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NCI Library
AN EXAMINATION OF THE RELATIONSHIP BETWEEN CREDIT
DEFAULT SWAPS AND EQUITY PRICES.
AUTHOR: DWAYNE MCNICHOLAS
PROGRAMME OF STUDY: MASTERS IN FINANCE
YEAR 2006
' National Colleger Ireland
School of Business & Humanities
National College of Ireland
2006
DECLARATION:
I hereby certify that this material, which I submit for assessment of the programme of
study leading to the award of a Masters in Finance is entirely my own work and has not
been taken form the work o f others, and to the extent that such work has been cited and
acknowledged within the text of my work.
Signed: 0-0
Date: «3-OQ4>
Student Number: L j-O
ABSTRACT:
This paper analyses the empirical relationship between credit default swap spreads and
equity prices at an individual firm level during the period Jan 2000 to Jun 2006. Using
samples from a data set of 250 of the most liquid, publicly quoted names in the credit
default swap market, I found there to be a statistically significant inverse relationship
between these two financial instruments. Additionally, I found that this relationship
changes when there is speculation that an individual firm may be purchased by means of
a leveraged buyout. During this period of speculation, the relationship is positive until
the company is taken private or until the speculation recedes. In the event of the
speculation being eliminated, I found that the relationship reverts to being negative.
TABLE OF CONTENTS:
I. INTRODUCTION:.......................................... ................................................................................................ .. 1
A) CREDIT DEFAULT SWAPS:........................................................................................................................2
What is a Credit Default Swap? ....................................................*.......................... ............ , ............................................................ 2
History o f CDS .................................. .......... ..*......................................... ,.................................................................................................... 2
Main participants in the CDS M arket........................................................................................................................ ........................ 3
Why use a CDS?................................... ........... . ......... .................*.................................................................................................................4
What happens when there is a credit event? ....................................................................................................................................5
Pricing CDS:......................................................................................................................................................................................... ............ 6
B) EQUITIES.........................................................................................................................................................7
History o f Equities:............................................ .......................................................... ......................................................................... •........... ♦♦................. . . . . . . . . 7
Why invest in Equities? .................................................................... ........................................... ........................ ......... *.......— ......... 7
B) LEVERAGED BUYOUTS..............................................................................................................................8
What is a Leveraged Buyout? ............................ .. .............................................. .....................................................................................8
History o f LB O s: ............... ......... *........... *........................................................................................................................................................ .......... 9
Main Participants in the Private Equity Market:............ *........... - ........................................................................................10
Recent LBO Activity:............................................................................................................................................................................. . 10
II. HYPOTHESIS:...................................................................................................................................................12
IH. LITERATURE REVIEW:............................................................................................................................. 12
Equities and Bonds: ...................................................................... .. ..................................................... ...................................................... 12
Equities and CDS:...... .. ................................................................................................................................. *...........................................13
Bonds and CDS:...................... ............ ...................................................................................................................................................... 14
IV. RESEARCH METHODOLOGY:................................................................................................................ 16
Collecting the D ata:......................................................................................................... ...........T......... ................................................. 16
Selecting Sample Companies:...................................... .......................................... .. ........................... ...............................................17
Testing the Data:..............................................................................................................................................................................................18
V. FINDINGS:.........................................................................................................................................................19
What is relationship between equity prices and CDS spreads? ............................................ .................... .................19
What happens the relationship in a LBO situation? ................................................................. ........................ ........... . 20
VI. CONCLUSION:............................................................................................................................................... 24
VII. REFERENCES:................................................................................................................. .............................25
VIII. BIBLIOGRAPHY 28
APPENDIX A: COMPANIES FOR WHOM DATA WAS COLLECTED:........................................... 29
APPENDIX B: SAMPLE OF INPUT DATA....................................*............................................................ 33
APPENDIX C: COMPANIES ELIMINATED FROM ORIGINAL DATA.............................................34
APPENDIX D: REGRESSION ANALYSIS OUTPUTS............................................................................... 35
APPENDIX E: MARKS & SPENCER GROUP LBO SPECULATION HISTORY..............................50
APPENDIX F: MARKS & SPENCER REGRESSION ANALYSIS OUTPUT........................................51
APPENDIX G: CDS INDICES CONSTRUCTION INFORMATION...................................................... 54
APPENDIX H: RATINGS DEFINITIONS..................................................................................................... 56
FIGURES/TABLES:
Figures:F ig u r e 1: H o w a CDS C o n t r a c t w o r k s ..................................................................................................................................2
F ig u r e 2: P a r t ic ipa n t s in t h e CDS M a r k e t a s o f D e c e m b e r 2005 , in b il l io n s o f US D o l l a r s ........... 4
F i g u r e 3: l b o a c t iv it y 1998 - p r e s e n t ...............................................................................................................................11
F ig u r e 4 : P r iv a t e Eq u it y - N ew F u n d s 1998 -2 0 0 5 ........................................................................................................ 11
F ig u r e 5: M&S Eq u it y P r ic e v .’s CDS P r ic e 2001 - P r e s e n t ...................................................................................50
F ig u r e 6: M o o d y s In v e s t o r S e r v ic e C r e d it Ra t in g S c a l e ....................................................................................56
F ig u r e 7: S& P Ra t in g s D e f in it io n s .......................................................................................................................................57
Tables:T a b l e 1: B r e a k d o w n o f C o m p a n ie s in CDS In d ic e s : ............................................................................................................16
T a b l e 2: B r e a k d o w n o f C o m p a n ie s s e l e c t e d f o r t e s t in g : ......................................................................................17
T a b l e 3: C o m p a n ie s s e l e c t e d a s s a m p l e s fo r t e s t in g ................................................................................................ 18
T a b l e 4: Re g r e s s io n A n a l y s is O u t p u t s : ............................................................................................................................19
T a b l e 5: R e g r e s s io n a n a l y s i s R e s u l t s f o r LBO C o m p a n y (M & S )..................................................................... 21
I. INTRODUCTION:
Empirical studies suggest that there is a close link between equity prices and debt prices as
their value depends on the market value of the firm’s assets and on the distribution of that
market value. What is less obvious is the relationship between these instruments and other
derivative products referencing the same company. In particular, the relationship between
the heavily growing credit derivatives market and traditional equity markets has only been
explored on a limited scale so far. For this reason, I propose to empirically analyse the
movement of single name credit default swaps and the movement of equity prices at an
individual firm level, thus investigating if and how these markets are connected.
After analysing this relationship, I propose to investigate its properties further under a
leveraged buyout. In recent years, there has been an upsurge in private equity activity and
leveraged buyout scenarios. This growth has been fuelled by, (a) historically low
borrowing costs making purchases cheaper and (b) rising stock markets making it easier to
sell assets at a profit thus giving returns to their investors. In total, there are 3,000 private
equity firms world-wide all aiming to deliver superior returns as investors to take
advantage of new and exotic financial instruments. These investors are typically looking
for higher returns than usually available from the stock market.
In order to investigate this in a clear and comprehensive manner, it is necessary to structure
the remainder of this paper in the following order:
■ The remainder of chapter I introduces credit default swaps, equities and leveraged
buyouts, each section explaining how they work and who the main participants are
in each market.
■ Chapter II states my hypothesis
■ Chapter III reviews previous literature in the area.
■ Chapter IV explains the methods used in gathering, selecting and testing the input
data for my analysis.
■ Chapter V details the findings of my research.
■ Chapter VI outlines my conclusions.
A) CREDIT DEFAULT SWAPS:
IVhat is a Credit Default Swap?
Credit Default Swaps (CDS) are a new form of credit derivative, which enables investors to
transfer credit risk (the risk of a company defaulting on its debt obligations). A CDS is an
insurance contract that provides insurance against default by a company or a sovereign
entity. The company is known as the reference entity and the default by the company is
known as a credit event. The CDS protects the buyer against losses from a credit event
associated with an underlying reference entity. In exchange for credit protection, the buyer
of a default swap pays a regular premium to the seller of protection (“investor”) for the
duration of the contract. Figure 1 gives a graphical representation of how a CDS contract
works.
ReferenceEntity
ProtectionDefault swap spread
I®#©! if ProtectionBuyer Seller
Ai
111iiL____
11
Contingent payment of loss following a credit event by the reference entity
Figure, I: How a CDS Contract works.
History o f CDS
CDSs were first developed for bonds, loans and similar instruments related to central bank
transactions only. Corporate entities soon constituted an additional market and by the late
1990s, firms begun to use CDS to buy protection for highly rated investment-grade1
1 Investment grade rating if held is a company or an issuance of debt is rated between Aaa and Baa by
Moodys or between AAA and BBB by Standard & Poor’s. Please refer to Appendix H for more detail.- 2 -
borrowers. In doing so, these firms could choose to increase their exposure to a firm by
selling CDS protection or choose to reduce their exposure to a firm by buying protection.
The notional amount of outstanding CDS contracts2 has grown exponentially since the
inception of the product, more than doubling in 2005 alone. The notional amount of CDS
contracts outstanding stands at $14 trillion3 as of 30-Dec-2005, up from $6.37 trillion at the
end of 2004. (Most of the initial development in the CDS market was in single-name
contracts. However, since late 2003 there has also been increasing activity in contracts
related to CDS indices. The Bank of International Settlements (BIS) statistics indicates that
the total notional amount outstanding of single- and multi-name default swaps was $10.2
trillion and $3.5 trillion respectively as of Dec 2005). Yet when compared to the combined
notion amounts of interest rate, equity index and currency contracts outstanding of $429
trillion4, the CDS market is still relatively small.
Main participants in the CDS Market
CDS contracts were thought to be most widely used in the banking system and the most
recent release of CDS statistics from the BIS confirms this. These statistics also provide a
finer breakdown of the counterparties than previously available. The data confirms the
impression that the CDS market, like most other OTC markets, is largely an interbank
market. As can be seen from figure 2, at the end of 2005, roughly two thirds of all
outstanding positions were between reporting dealers and a further quarter were between
reporting dealers and other banks or securities firms. The top three counterparties in 2004
were Deutsche Bank, Morgan Stanley and Goldman Sachs who accounted for 26% of all
contracts, with the top 10 counterparties accounting for 70% of all contracts5
2 In a standard contract, payments by the buyer are made quarterly or semi-annually in arrears on an
actual/360day basis. If the reference entity defaults, there is a final accrual payment, payments then stop and
the contract is settled.
3 The total notional amount outstanding is calculated as the sum of contracts bought and sold minus half of the
sum of contracts bought and sold between reporting dealers. Source: BIS Quarterly Review of Derivatives
Markets, June 2006, Chapter 4.
4 As of 31 March 2006. Source: BIS Quarterly Review of Derivatives Markets, June 2006.
5 Source: Fitch Ratings Presentation to Professional Risk Managers International Association, February 2006
-3 -
Notional Amounts Outstanding BoughtNon-
Financial Institutions,
358Insurance &
Financial Guarantee firms, 176
Notional Amounts Outstanding SoldNon-
Financial Institutions,
277
Insurance &Financial
Guarantee firms, 59
Figure 2: Participants in the CDS Market as o f December 2005, in billions o f US Dollars.
Source: Bank fo r International Settlements
Why use a CDS?
There are a variety of reasons why banks, other financial institutions and investors might
use CDS. These reasons can be broken down into three main categories:
1. Risk Management: CDS can be used as a way of increasing or decreasing credit
exposure to the reference entity6. For example, take a relationship bank that may have
lent money to a corporate client with which it has a long-standing relationship. After
lending this money, the bank takes a negative view on the future of that corporate. In
this case, a CDS can be used to reduce the bank’s exposure to that client by purchasing
protection. In doing this, the bank eliminates the risk of losing money through any
potential default by the corporate, yet it is able to maintain the long-standing
relationship because the client may not be aware of this hedging. This also frees up
regulatory capital, which gives the bank the ability to pursue other lines of business that
may be more lucrative. The opposite is also true, the same bank can increase its
exposure to an existing corporate or take on new exposure to corporate names that fit
the banks risk appetite but with who they may not have a relationship.
2. Trading Credit Risk: An institution/investor can trade credit risk more efficiently using
CDS. Commissions and other trading fees are less in the CDS market because of
6 Source: ECB Publishing: Credit Risk Transfer by EU Banks: Activities, Risks and Risk Management (May
2004).
- 4 -
increased liquidity. CDS also allow investors to take either a long or a short view on a
credit. This is not possible in traditional debt markets.
3. Arbitrage Opportunities: Institutions/Investors can use CDS in an effort to benefit from
arbitrage opportunities in the market. These arbitrage opportunities may occur between
differing lengths of CDS contracts or between a CDS contract on a particular reference
entity and a bond that has been issued by that entity.
What happens when there is a credit event?
There are two types of settlement when credit default swaps are used: cash and physical.
1. Cash Settlement:
Under a cash settlement, there is no delivery of the reference obligation (the reference
obligation is a debt instrument issued by the reference entity). A market auction of the
reference obligation takes place after the credit event occurs, the benefits of which go to
the protection buyer. The seller of protection then makes a cash payment to the buyer
for the difference, if any, between the calculation amount and the recovery value of the
reference obligation.
2. Physical Settlement:
Under a physical settlement, the buyer of protection delivers title to its claim against the
reference entity (the reference obligation) to the seller of protection. The provider of
protection then has a claim on the reference entity. The provider of protection then
makes a cash payment to the buyer of protection for the calculation amount (i.e.,
nominal value of the bonds) less any accrued fee payable.
As a specific example7, suppose that on January 23, 2002, a protection buyer wishes to buy
five years of protection against the default of the Worldcom 7.75 pcrcent bond maturing
April 1, 2007. The buyer owns 10,000 of these bonds, each having a face amount of
$1,000. Thus, the notional value of the buyer’s position is $10,000,000. The buyer
contracts to buy full protection for the face amount of the debt via a single-name credit
default swap with a 169 basis point premium. Thus, the buyer pays a premium of
7 Example taken from Longstaff, Mithal and Neis, 2003.
- 5 -
A/360xl69, or approximately 42.25 basis points per quarter for protection, where A
denotes the actual number of days during a quarter. This translates into a quarterly payment
of A/360 x $10, 000, 000 x .0169 = A/360 x $169, 000. So when Worldcom filed for
bankruptcy, under a physical settlement, the buyer delivers the 10,000 Worldcom bonds to
the protection seller and receives a payment of $10,000,000. Credit events that typically
trigger a credit-default swap include bankruptcy, failure to pay, default, acceleration,
repudiation or moratorium, or a restructuring.
Pricing CDS:
The price of a CDS contract, or the cost to buy protection on a reference entity, is known as
the CDS spread. In theory, the /V-year CDS spread should be close to the excess of the
yield on a A^-year bond issued by the reference entity over the risk-free rate (Hull, Predescu
& White, 2004). A number of other researchers have independently carried out related
research. Longstaff, Mithal and Neis (2003) assume that the risk-free rate is the U.S.
Treasury rate and fmd significant differences between CDS and bond yield spreads.
Blanco, Brennan and Marsh (2003) use the swap rate (LIBOR8) as the risk-free rate and
find credit default swap spreads to be quite close to bond yield spreads. Houweling and
Vorst (2002) confirm that the credit default swap market appears to use the swap rate rather
than the Treasury rate as the risk-free rate.
In practice, CDS spreads are then added to LIBOR to get the total cost of purchasing
protection (or the total income from selling protection) through a CDS contract (i.e.
EIRCOM 5yr CDS bid/ask of LIBOR +267/287bps).
8 LIBOR: London Interbank Offered Rate is published by the British Bankers Association (BBA) shortly after
11:00 each day, London time, and is a filtered average of inter-bank deposit rates offered by designated
contributor banks, for maturities ranging from overnight to one year.
- 6 -
B) EQUITIES
History o f Equities:
Unlike the recent developments in CDS, equities or stocks have existed in some form for
hundreds of years. The first actively traded U.S. stocks, floated in 1791, were two banks:
the Bank of New York and the Bank of the United States. The creation of equities as an
investment allowed the public to own easily tradable shares of a company for the first time.
Before 1801 there were over 300 corporations chartered in the U.S., yet fewer than 10 had
securities that traded on a regular basis and two-thirds of those were connected with
transportation. In the early nineteenth century, the most important stocks were financialti_
institutions: banks and later, insurance companies. Throughout the 19 century, stocks• • • • th were seen to be for speculators and insiders and it wasn’t until the 20 century that people
came to realise that stocks, as an asset class, might be suitable investments under certain
economic conditions. Throughout the 21st century, investing in stocks has become
ubiquitous as markets became more heavily regulated and transparent and the public
became more familiar with how stocks functioned. As Roger Lowenstein commented
about the American public in 1996, “Investing in stocks has become a national hobby and
a national obsession... To update Marx, it is the religion o f the masses”.
Why invest in Equities?
People invest in stocks for one of the following reasons or a combination of the following
reasons. Firstly, capital appreciation. People invest in stocks with the belief that the stock
price will increase over time as the company delivers profitable performance and reinvests
its profits into growing the company. The more an investor expects a company to grow,
the more they are willing to pay for the stock. Secondly, dividend yields. Investors are
attracted by the income received from amount paid out in dividends each year. Whether a
company has a high dividend depends on its industry and its stage in the growth cycle. It is
more typical to see mature, non-cyclical companies with high dividends, as they will have
more stable cashflows. Investors also look to stocks as being a hedge against inflation.
Historical evidence suggests that the returns on stocks over long periods of time have kept
pace with inflation. Since stocks are claims on the earnings of real assets (assets whose
- 7 -
value arc intrinsically linked to labour and capital), it is reasonable to expect that their
long-term returns would not be influenced by inflation. Finally, there arc psychological
reasons why some investors look to equities. This could be due to popularity of equities at
a given time or pure speculation.
B) LEVERAGED BUYOUTS
What is a Leveraged Buyout?
Leveraged Buyouts (LBOs) are one area in the broader industry of Private Equity. Private
equity also includes venture capital and can be described as medium to long-term finance
provided in return for an equity stake in potentially high growth unquoted companies. A
Leveraged Buyout (LBO) is a takeover of a company, using a combination of equity and
borrowed funds. Generally, the target company's assets act as the collateral for the loans
taken over by the acquiring group. The acquiring group then repays the loan from the cash
flow of the acquired company. LBOs can generally be separated into two categories: (i)
buying a private company or (ii) buying a public company and taking it private (sometimes
known as “take public to private” or “take private” transactions). The latter type of
transaction is becoming increasingly popular throughout Europe and the L.S. In most
LBOs, public shareholders receive a premium to the market price of the shares. The
acquiring groups objective is to exit the investment after three to five years realising,
typically, an internal rate of return of greater than 20%9. Assumptions regarding business
performance, the exit strategy, and the period between acquisition and exit are critical to
determining an appropriate capital structure and potential returns to equity investors. The
acquirer will generally look to create value through some/all if the following mechanisms:
■ An increase in the underlying operating and financial performance of the assets
acquired.
■ Repayment of debt through cashflow generated while owning the asset.
9 Source: JP Morgan European Credit Research, LBO Structuring-Behind die Scenes, Jan 2006.
- 8 -
■ Increased multiple on sale of the business (i.e. the acquiring group bought the
company for a multiple of 8.Ox EBITDA and sell for 10.Ox EBITDA).
Many companies that become targets of LBOs have common characteristics. These
include10:
■ Steady and predictable cash flows.
■ A clean balance sheet with little debt.
■ A strong, defensible market position.
■ Limited working capital requirements.
■ Minimal future capital requirements.
■ A heavy asset base for loan collateral.
■ Assets that the company can divest of.
■ A strong management team.
■ A viable exit strategy.
■ Synergy opportunities.
■ Potential for cost reduction.
History o f LBOs:
LBO’s first came to prominence in the 1980’s when LBO firms and their professionals
were the focus of considerable attention, mostly negative. However, the first LBO is
believed to have been carried out in the years following World War II. Before the 1980’s,
LBO’s were commonly known as a “bootstrap acquisition” and were little more than
obscurc financing. After the end of World War II, the Great Depression was still relatively
fresh in the minds of America’s corporate leaders few companies relied on debt as a
significant source of funding. At the same time, American business became caught up in a
wave of conglomerate building that began in the early I960’s. Throughout this period,
middle management in companies grew, and profitability declined. In the late 70’s and
early 80’s, newly formed companies such as Kohlberg Kravis Roberts and Thomas H. Lee
Company saw an opportunity to profit from this inefficiency and the modem LBO was
10 Source: Centre for Private Equity and Entrepreneurship, Tuck School of Business at Dartmouth College,
Note on Leveraged Buyouts” Sept 2003.
- 9 -
bom. Many early LBOs were motivated by profits available from buying entire companies,
breaking them up and selling them in pieces, however, in recent years this is no longer the
primary motivation. Nowadays, in many cases the motive is to buy the company, take it
private and in doing so, reduce the amount of scrutiny the company is under from the
market. The firm then goes about eliminating inefficiencies within the company with the
intention of re-floating the company on the market and exiting with the funds raised from
the floatation. The largest LBO in history was carried out in 1989 when Kohlberg Kravis
and Roberts purchased RJR Nabisco for €25 billion. The deal was ultimately unsuccessful
and in 1999, the tobacco company spun off the food and cracker company.
Main Participants in the Private Equity Market:
There are about 3,000 private equity firms world-wide. In the U.S. alone, there are an
estimated 1,607 private equity firms, up from 773 in 1995, according to Thompson
Financial. The top 5 market participants are Carlyle Group, Blackstone Group, Kolhberg
Kravis Roberts, Texas Pacific Group & Thomas H. Lee which together raised $123 billion,
equivalent to 47% of all funds raised in 200511.
Recent LBO Activity:
LBO activity has been extremely strong over the past two years and 2006 is expected to be
another record year with $95 billion spent on LBOs up to the end of May (See figure 3).
There are a number of reasons why this growth has occurred in the LBO market including;
(i) historically low interest rates both in the U.S and in Europe, (ii) rising stock markets
make it easier to profit from sales and (iii) increased appetite for this type of risk from
investors who look for higher returns than those available from the stock market. In
research carried out by Lehman Brothers12, the amount of equity capital raised in the
previous year was one of the leading factors in predicting the number of LBOs each year
between 1990 and 2005. Using correlation, they found that the amount of equity raised
explained 53% of the number of LBOs in the subsequent year. New funds raised by private
11 Source: Wall Street Journal: “Is the Boom in Buyouts Good for Business?” June 2006
12 Source: Lehman Brothers Quantitative Credit Strategy paper, May 2006.
- 1 0 -
equity firms (includes venture capital firms and buyout firms) have been growing strongly
since 2003 (See figure 4), and that these firms raised a record $261 billion in 2005. When
we take this into account the expectation that 2006 will be a record year is reinforced.
5300
$250
-S' $200CC| $150ViS $100
$50
$0
JSP
Private Equity fund raising trends 1998 - 2005
E32
3 ?N* ^Source: Price WaterhouseCoopers Global Private Equity Report 2005
\$261
/3ED
Figure 4: Private E quity-N ew Funds 1998 -2005
- 11 -
I propose the following hypothesis:
H I: What is the relationship between equity prices and credit default swap spreads?
As a result of this relationship and as a sub-hypothesis, I also propose to investigate the
following hypothesis:
H2: If there is speculation that a company will be acquired through a leveraged buyout
(LBO): does this relationship change?
III. LITERATURE REVIEW:
In comparison to other areas in finance and since CDSs are relatively new financial
instruments, there is limited research to date covering this specific topic, although research
in continuing in this area. When you narrow this research down to the specific area, which
I propose to investigate throughout this paper, there is no one paper written to date which
specifically addresses all the topics. However, upon researching the broader area of credit
derivatives, equities and leveraged buyouts, I found there to be papers that address related
topics. Some of these papers examined the relationships between equities and bonds,
between bonds and CDS, and equities and CDS (although this research does not address the
specific area being examined in this paper). Therefore, I will be reviewing these papers
under the headings relating to the areas they cover.
After searching extensively, I can find no research in the area of how LBOs effect the
relationship between CDS prices and equity prices. All the papers uncovered have been in
relation to the valuation of a leveraged buyout. As this topic is not linked to my research, I
have chosen to omit it.
Equities and Bonds:
There have been several studies that link the credit default swap market, the bond market
and the equity market. Fama and French (1993) investigate which risk factors are able to
explain monthly returns of stock and corporate bond portfolios in the period 1963 - 1991.
They identify three stock market factors (overall excess market return, firm size and book-
II. HYPOTHESIS:
- 1 2 -
to-market equity ratio) and two bond-market factors (term structure spread and default risk
spread) whereas the two bond-market factors establish the link between both markets.
Alexander, Edwards and Ferri (2000) investigate the relationship between daily stock and
high-yield bond returns at the individual firm level during the period 1994-1997. They find
positive but economically weak correlation between daily high-yield bond returns and
firms’ stock excess returns.
Equities and CDS:
In the area of equities and CDS, Zhang, Zhou and Zhu (2005) analysed how a structural
model with stochastic volatility and jumps implies particular relationships between
observed equity returns and credit spreads. They found that volatility risk alone predicts
50% of CDS spread variation, while jump risk alone forecasts 19%. After controlling
credit ratings, macroeconomic conditions, and firms’ balance sheet information, they could
explain 77% of the total variation. They also found that marginal impacts of volatility and
jump measures increase dramatically from investment grade to high-yield entities.
Longstaff, Mithal, and Neis (2003) examine weekly lead-lag relationships between CDS
spread changes, corporate bond spreads and stock returns of US firms. They fit a reduced-
form model to corporate bond yields and solved for the credit default swap premiums they
imply. They then compared the implied market premiums to actual market premiums.
They find that both Stock and CDS markets lead the corporate bond market. However,
they found no clear lead of the stock market with respect to the CDS market or vice versa.
Abid and Naifar (2005) studied the impact of stock returns volatility of reference entities
on credit default swap rates using a data set from the Japanese market. Using a copula
approach13, they model the different relationships that can exist in different ranges of
behaviour. They found that the dependence structure between credit default swap rates and
stock return volatility is asymmetric and positive and display right tail dependence. They
also found that companies with higher credit ratings present a weaker dependence
13 A copula is a statistical measure that represents a multivariate uniform distribution, which examines the
association or dependence between many variables. Source: www.investopedia.com
- 13 -
coefficient and the impact of stock return volatility on credit default swap rates is higher for
the lowest credit rating class.
Bystrom (2005) provides evidence of a link between the Dow Jones ITraxx CDS index14
market and the stock market. This study took a market level perspective (vis-a-vis a
individual firm level) and found that a correlation study reveals a tendency for ITraxx CDS
spreads to narrow when stock prices rise and vice versa. Furthermore Bystrom found
evidence that firm-specific information was embedded in stock prices before it was
embedded into CDS prices. Stock price volatility is also found to be significantly
correlated with CDS spreads. Bystrom found that as stock price volatility increases, credit
spreads increase and vice versa.
Zhang (2004) documented the existence and heterogeneity of within-industry credit
contagion for major credit events, including Chapter 11 bankruptcies, Chapter 7
bankruptcies and other significant jump events using a comprehensive data set of credit
default swap spreads. Furthermore, Zhang uncovered evidence that the co-movement of
credit risk within the same industry is attributable to both common industry risk and
contagious spillovers. He also reported evidence that credit contagion is captured in the
CDS market in an earlier, cleaner and stronger was than in the stock market.
Bonds and CDS:
Blanco, Brennan, and Marsh (2004) followed Collin-Dufresne, Goldstein, and Martin
(2001) in analysing determinants of CDS spread changes and coiporate bond spread
changes. They found that the impact of firm-specific stock returns is stronger on CDS
spread changes than on corporate bond spread changes.
Longstaff, Mithal, and Neis (2003) examined whether credit protection was priced
consistently in the corporate bond and credit derivatives market. They found clear
evidence that the implied cost of credit protection is significantly higher in the corporate
bond market than in the credit derivatives market. They concluded that the potential
explanation for the higher cost of credit protection implied by corporate bonds may be due
14 Dow Jones ITraxx is a CDS index comprised of the top 125 most liquid CDS names in Europe across six
sectors. Please refer to Appendix VII for more information on its construction.
- 14-
to significant tax-related and liquidity components built into the spreads of these corporate
bonds.
Hull, Predescu, and White (2004) examined the relationship between CDS spreads, bond
yields, and credit rating announcements.
The study by Bystrom (2005) is the most closely related paper to my proposed research
where he assesses the relationship between the ITraxx CDS market. However, there are
distinct differences between Bystrom’s research mid my proposed research. To start, I
propose to examine the relationship at an individual firm level before further this research
and assessing the relationship in an environment where there is LBO speculation
surrounding a firm.
- 1 5 -
IV. RESEARCH METHODOLOGY:
Collecting the Data:
In order to carry out my research it was necessary to collect both historical CDS price data
and historical equity price data for a pool of companies. In order to get reliable data it was
necessary to choose companies that were publicly quoted and liquid in the CDS market.
Consequently, the best course of action was to use the companies who make up the Dow
Jones CDX Investment Grade Index (North America) and the Dow Jones ITraxx
Investment Grade Index (Europe). In doing so, this ensures the liquidity and validity of the
data. Each index comprises of the top 125 liquid names in the CDS market throughout
North America and Europe (giving a total sample of 250 companies) and is re-balanced
every six months. The companies that make up the index are from a variety of different
business areas but they are placed into six broad sectors. These sectors are; (i) Auto; (ii)
Consumer; (iii) Energy; (iv) Financial; (v) Industrial; (vi) Telecommunication, Media and
Technology (TMT). (Please refer to Appendix G for more information on the construction
of these indices). A breakdown of the companies by sector can be seen in table 1, note
there are no auto companies in the American Index. This is because there are currently no
American auto manufacturers with investment-grade credit ratings since both General
Motors and Ford Motor Company were both downgraded to junk status in 2005. To
compensate for this, the number of companies operating in the other sectors has increased,
thus bringing the index back to equilibrium.
Table 1: Breakdown o f Companies in CDS Indices:
Auto Consumer Energy Financial Industrial TMT Total
European 10 30 20 20 20 25 125
North American 0 36 14 29 22 24 125
Total 10 66 34 49 42 49 250
% o f Total 4.0% 26.4% 13.6% 19.6% 16.8% 19.6% 100.0%
Having selected the companies that would form the pool, it was necessary to determine the
time frame for the analysis. For this, I have selected the starting point 1 January 2000.
There are two reasons why this point was chosen. Firstly and most importantly, the CDS
market was only developed in the late nineties and initially there was a lack of liquidity in
- 16-
the market. Consequently, single name CDS pricing experienced large degrees of
volatility, which may not have truly reflected the volatility in the credit risk of the
underlying corporate. Secondly, what is now 5/4 years worth of data (284 observations)
will make my findings statistically significant.
The next step was to gather the raw data. To do this I used Bloomberg Professional
Service (“Bloomberg”). This software allowed me to collect weekly equity price data and
CDS price data for the pool of companies. When doing this, I chose to use the CDS mid
price for each company vis-a-vis the bid or offer, as this was the most conservative option.
In choosing the mid-price, this eliminated any degree of illiquidity that existed for each
company, as there is usually large differences between the bid and the offer price for
illiquid names, thus increasing the validity of my findings. (For a full list of the companies
that compose both indices, please refer to Appendix A).
After collecting this data, I was forced to eliminate 17 companies through lack of reliable
data (e.g. unreliable CDS Price or the company was no longer a public quoted company but
still had a CDS price because of debt outstanding). This left me with 233 companies from
which to take samples and test.
Selecting Sample Companies:
Utilising prudence and efficiency, it was necessary to take a fair and representative sample
of the different types of companies. To do this I broke the companies down by geography
and by sector and used the process of random stratified sampling to select sample
companies to test. A breakdown of the samples used by geography and by sector can be
seen in table 2. The list of companies selected for testing can also be seen in table 3.
Table 2: Breakdown o f Companies selected fo r testing:
Auto Consumer Energy Financial Industrial TMT Total
European 2 1 1 I 1 1 7
North American 0 2 2 1 1 2 8
Total 2 3 3 2 2 3 15
% o f Total 13.3% 20.0% 20.0% 13.3% 13.3% 20.0% 100.0%
- 17-
Table 3: Companies selected as samples fo r testing.
European North American
Auto Volvo AB
Volkswagen AG
Consumer PPR The Boeing Company
The Kroger Company
Energy National Grid Pic. Transocean Inc.
Valero Corp.
Financial Unicredito Italiano SpA American Express Company
Industrial Seimens AG Alcoa Inc.
TMT Vivendi SA Hewlett-Packard Co.
The Walt Disney Company
The companies selected in table 3 were used to test the relationship between the equity
price and the CDS price of the respective companies. However, as I mentioned before my
sub-hypothesis was examine if and how this relationship changed as a result of LBO
speculation surrounding the company and furthermore what happens if this speculation is
eliminated. To assess this I searched through the list of companies in both CDS indices
where there was speculation that a LBO would occur but where this speculation has since
ceased. I found this particularly difficult, as there were many companies who are currently
surrounded by LBO speculation, but where the outcome is unclear. As it is not possible to
prolong the research in order to see whether each company will be (a) bought-out and taken
private or (b) the LBO speculation receded it was necessary to choose a specific historic
example. One company fitted this profile: Marks and Spencer Group Pic (M&S).
Testing the Data:
To test the relationship between the variables 1 used SPSS. By inputting the equity price
data and the CDS price data from each of the selected companies in table 3, SPSS was able
to run regression analysis on the information. In doing this, I assumed the independent
variable to be the company’s equity price and the dependent variable to be the company’s
CDS price. This program analysed the data on this basis and returned statistics values such
as the R2, the F-Tcst, the dependent variables coefficient and the t-statistic. Using this
information, I was able to interpret my findings.
- 18 -
V. FINDINGS:
What is relationship between equity prices and CDS spreads?
Based on statistical analysis, upon examining the relationship between equity prices and
CDS prices, I found there to be an inverse relationship. This means that for an increase in a
company’s equity price we can expect to see a decrease in that company’s CDS price. A
summary of the regression analysis results can be seen in table 4.
Table 4: Regression Analysis Outputs:
Geography Sector Company R2 F - Statistic Coefficient t-statistic Covariance Correlati
North American Industrial Alcoa Inc. 0.542 246.900 -1.982 -15.713 -31.061 -0.676
North American Financial American Express 0.686 454.508 -2.137 -21.319 -51.006 -0.807
North American TMT Disney 0.747 730.810 -7.677 -27.033 -320.238 -0.803
North American TMT Hewlett Packard Inc. 0.440 164.422 -4.509 -12.823 -35.651 -0.567
North American Consumer Kroger 0.097 23.860 -3.897 -4.885 -17.164 -0.426
European Energy National Grid Pic. 0.491 196.724 -11.748 -14.026 -12.094 -0.753
European Consumer PPR 0.653 337.232 -5.492 -18.364 -666.135 -0.807
European Industrial Siemens AG 0.370 148.212 -1.016 -12.174 -103.463 -0.841
North American Consumer The Boeing Company 0.572 278.356 -1.561 -16.684 -220.352 -0.732
North American Energy Transocean 0.536 202.430 -0.526 -14.228 -2.260 -0.528
European Financial Unicredito Italiano SpA 0.233 67.582 -7.447 -8.221 -408.923 -0.579
North American Energy Valero 0.296 87.735 -1.976 -9.367 -465.452 -0.849
European TMT Vivendi SA 0.369 126.812 -30.446 -11.261 -82.323 -0.738
European Auto Volkswagen AG 0.698 572.687 -1.421 -23.931 -92.769 -0.883
European Auto Volvo AB 0.595 364.017 -2.350 -19.079 -68.742 -0.877
When we break this results down and examine them in more detail, we can see that all of
the independent variable (equity price in this case) coefficients are both negative and are
statistically significant. These two results are key in proving that both a negative
relationship exists and that this relationship is statistically significant. In examining the R2
output for each of the companies, we can see that in 14 out of the 15 samples taken the
movement in equity price displays strong explanatory power in the movement in CDS
- 1 9 -
pricc. It is also important to note that these results were consistent throughout all the
sectors.
Upon reflection, this outcomc makes sense. If we think of circumstances, where a
company’s equity price increases there is usually positive news behind the movement.
This movement could be explained by an event in the company’s microenvironment such
as improved sales in the previous quarter or an approved patent for a new product which
investors believe will lead to increased returns in future. The increase could also be caused
be an event in the company’s macro-environment such as a favourable ruling in the
company’s regulatory environment. In any event, if we think of how any such news would
effect the company’s credit standing, any improvement in the company’s financial metrics
will reduce the risk of the company defaulting on it’s debt obligations. Logically, if there
were a reduced risk of the company defaulting, this would be reflected in the price for a
purchaser of CDS protection.
What happens the relationship in a LBO situation?
As I described in my research methodology there was one company in my pool of data
which fitted this specific profile. This company was Marks and Spcncer Group Pic.
(M&S). In May 2004, speculation mounted that billionaire Philip Green, owner of other
UK retail stores, would purchase M&S via a leveraged buyout. This speculation receded in
July 2004 when Green could not get co-operation from the company board. (For more
information in relation to the specific details of this LBO bid, please refer to Appendix E).
During the analysis of M&S’s data, it was prudent to analyse the data before any approach
from Green and after the approach became public knowledge. Therefore, the period from
01-Jan-2000 to 27-May-2004 became my first period to analyse. In examining this first
period, I found that the equity price coefficient to be negative (consistent with broader
analysis), although the t-statistic cannot be deemed statistically significant. Furthermore,
the R2 in that period is only 0.003, meaning that the movement in share price does not
display good explanatory power in the movement in CDS pricc. Although this result does
not show the same significance as the broader analysis my main research, I feel that the
- 2 0 -
breadth of that analysis proves that the inverse relationship exists. In this case M&S (in the
period before any LBO speculation) is an outlier.
1 proceeded to examine the relationship after the news of the Green approach became
public and decided to break this period into two sub-periods also. I decided to test the data
from 27-May-2004 (date of news breaking) + 1 month and found that the relationship had
turned positive. I then tested the data from 27-May-2004 + 2 months and the relationship
remained positive. I continued to test in this manner and found that after 3 months the
relationship returned to being negative. This negative relationship is consistent with my
findings in my main research
Therefore, for the period from Jan-2000 to 27-May-2004, I found that while the data
returned a negative relationship the results are not statistically significant. For the period
from 28-Aug-2004 to present, I found that the relationship is consistent with my main
research. In this case, the coefficient of the independent variable (equity price) was -• « « • 924.391 and with a t-statistic of -41.103, this can be deemed statistically significant. The R
in this case was 0.866 demonstrating that the movement in equity price is a good predictor
for the movement in CDS price.
For the period between 27th May 2004 and 27th August 2004 the analysis displayed a
positive relationship, with a coefficient of 494.167 and a t-statistic of 6.152 making it• • • • 2 , , ,
statistically significant. With an R value of 0.759, it showed that a movement in equity
price during this period could predict the movement in CDS price also. A summary of the
analysis can be seen in table 5.
Table 5: Regression Analysis Results fo r LBO Company (M&S)
R2 F - Statistic Coefficient t-statistic Covariance Correlation
Prior to any LBO speculation 0.003 0.139 -3.454 -0.373 0.225 0.087
During period o f LBO speculation 0.759 37.846 494.167 6.152 7.491 0.871
Period after LBO speculation receded 0.866 594.927 -24.601 -24.391 -41.103 -0.931
Having analysed this output, I began to investigate further why this may be the case. Why,
if there is speculation of a company being purchased via a LBO, would the relationship
-21 -
between the equity price turn from negative to positive? I found there to be a number of
reasons why this would happen:
1. From a equity holders standpoint:
When a private-equity firm approaches a company, the firm will be forced to pay a
premium over the current share price in order to gain the approval of the shareholders.
Studies of Mergers & Acquisitions (M&A) which includes private equity acquisitions,
have shown that the premiums15 paid for targets stood at c.25% in 2005. This figure is
down from c.50% in 200016. When we take this into account we can see why the share
price would increase post-announcement of any buyout. Based on empirical research,
investors buy the equity in the hope that they will make significant returns between the
period of the transaction announcement and when the buyout transaction is completed.
2. From a CDS holders standpoint:
The prospect of a LBO from a CDS holder’s standpoint is unfavourable. By its nature,
a LBO will increase the amount of debt in the company; this will reduce the company’s
financial flexibility through increases in repayments. Above all, increased debt will
increase the likelihood of a credit event occurring. However, after further examination,
this is not the only reason that we could expect the CDS price to increase. The CDS
price can increase due to technical reasons. The problem surrounds the reference
obligation. The reference obligation determines the type and seniority of debt
obligation issued by the reference entity that can be delivered to the seller of protection
under a credit event. In a LBO situation, the debt that the private-equity firm raises
may rank more senior than that of the reference obligation. This is often the case in an
LBO situation because the debt raised to fund the buyout is secured on the assets of the
company, whereas the reference obligation in a CDS contract ranks as senior unsecured
debt in the majority of cases. Therefore, if a credit event occurs and the LBO debt
ranks more senior than the reference obligation. This increases the risk that the
15 Premium is relative to the targets share price four weeks prior to announcement for deals over US$250
million. Source: Goldman Sachs Global Strategy Research, April 2005.
16 Source: Goldman Sachs Global Strategy Research April 2005.
- 2 2 -
recovery value of the reference obligation is diminished as a result of the secured debt
being repaid first.
While the findings from an equity standpoint are not surprising, the CDS-holder findings
were unexpected at the outset of this research.
VI. CONCLUSION:
In this paper, I primarily investigated the empirical relationship between credit default
swap prices and equity prices at an individual firm level for an international sample over
the period 1 Jan 2000 to 16 June 2006. Secondary to this research, and because of the
aforementioned relationship, I investigated if and how the relationship changes where there
is speculation that an individual firm may be purchased through a leveraged buyout.
Throughout the course of my research, I found that over the period, in all samples across all
industry sectors, there was a negative relationship between the company’s equity price and
CDS price. This means that if the company’s equity price increases we can expect to see
the company’s CDS price declining. Averaging all the R values from the data selected, I
found that the movement in equities could explain 49% of the movement in CDS prices.
Furthermore, it was found that should the market believe that an individual firm would be
purchased via a LBO, this specific negative relationship, i.e. between CDS and Equity
prices, behaves uncharacteristically. I found that, during the period of this speculation, the
relationship is positive and both prices move in the same direction. However, when this
speculation recedes, the relationship reverts to its original form: a negative relationship. In
investigating this area, one unexpected outcome was uncovered. This is the impact of the
reference obligation from the CDS-holders perspective in a LBO situation. There is a
possibility that the reference obligation in the terms of the CDS contract could become
subordinated to the debt used to finance the LBO. Because of increased debt a LBO would
place on the target company’s balance sheet, its financial flexibility is reduced and
therefore increasing the possibility of a credit event. This technical situation is shown to
have a major effect on the price of the CDS contract in a LBO environment.
This relationship between CDS prices and equity prices can be deemed conclusive.
However, due to the lack of companies that currently fit the profile of my LBO situation, I
feel that this area of my research could be examined in more detail in future. Activity in
the LBO market is currently at historically high levels and with the certainty that not all of
these LBO attempts will be successful, we are sure to see more companies that fit this
profile in the future. Therefore, I firmly believe this paper provides a good foundation for
more investigation in this area in the future.
- 2 4 -
VII. REFERENCES:
Abid, F. and Naifar, N. 2005, The Impact o f Stock Returns Volatility on Credit Default
Swap Rates: A Copula Study, University of Sfax, Tunisia
Artabane, A. et al. 2005, PriceWaterHouseCooper: Global Private Equity Report 2005
(Internet) www.pwemonevtree.com/exhibits/GPE Report 2005
Asquith, P. and Wizman, T.A., 1990, Event Risk, Covenants, and Bondholder Returns in
Leveraged Buyouts, Journal of Financial Economics
Bystrom, H. 2005, Credit Default Swaps and Equity Prices: The ITraxx CDS Index Market,
Department of Economics, Lund University
Etter, L. 2006, Is the Boom in Buyouts Good for Business, Wall Street Journal Online
Edition, 3rd June.
European Central Bank 2004, Credit Risk Transfer by European Banks: Activities, Risks
and Risk Management, 24 May, (Internet) www.ecb.int
Batterman, J., 2006, Presentation to Professional Risk Managers International Association,
13 February, Fitch Ratings Service. (Internet) www.fitchcdx.com
Horsley, R. et al. 2006, JPMorgan Credit Research: LBO Structuring, Behind the Scenes,
Research Report 26 January 2006, London.
Hull, H., Predescu, M. and White, A. 2004, The relationship between Credit Default Swap
Spreads, Bond Yields and Credit Rating Announcements, Joseph L. Rotman School of
Management, University of Toronto.
- 2 5 -
Hull, J. and White, A. 2003, The valuation o f Credit Default Swaps, Joseph L. Rotman
School of Management, University of Toronto.
Jin, L. and Wang, W. 2002, Leverage Buyouts: Inception, Evolution, and Future Trends,
Perspectives, Vol. 3, No. 6.
Longstaff, F.A., Mithal, S., and Neis, E. 2003, The Credit Default Swap Market; Is Credit
Protection Priced Correctly? Anderson school, University of California
Ng, C. et al. 2005 Goldman Sachs Global Strategy Research, Research Report 15 April
2005, London.
Micu, M. and Upper, C. 2006 BIS Quarterly Review, International Banking and Financial
Markets Developments, Chapter 4; Derivatives Markets, Basel, BIS Press &
Communications, (Internet) http://www.bis.Org/publ/qtrpdf/r qt0606.r)df
Moodys Investor Service, 2004, Moodys Ratings Symbols and Definitions, (Internet)
www.moodys.com
Norden, L. and Weber, M. 2004, The Comovement o f Credit Default Swap, Bond and Stock
Markets: an empirical analysis, Department of Banking and Finance, University of
Mannheim
O’Kane, D. et al., 2003 The Lehman Brothers Guide to Exotic Credit Derivatives, London,
Risk Waters Group
Standard & Poor’s Rating Service, 2006, Standard & Poor’s Ratings Definitions, (Internet)
www.ratingsdirect.com
Upper, C. and Gallardo, P. 2005 OTC Derivatives Market Activity in the first half o f 2005,
Basel, Bank for International Settlements Monetary and Economic Department
- 2 6 -
Zhang, G. 2004, Intra-Industry Credit Contagion: Evidence from the Credit Default Swap
Market and the Stock Market, University of California
Zhang, B. Y., Zhou, H. and Zhu, H. 2005, Explaining Credit Default Swap Spreads with
Equity> Volatility and Jump Risks o f Individual Finns, Bank for International Settlements
(BIS) Monetary and Economic Department, BIS, Press and Communications, Basel.
(Internet) www.bis.org/publ/workl 81 .pdf
- 2 7 -
Vni. BIBLIOGRAPHY
Anson, M., el al., 2004, Credit Derivatives: Instruments, Applications, ami Pricing, 1st
Edition, New Jersey, John Wiley and Sons Inc.
Benkert, C., 2004, Default Risk In Bond And Credit Derivatives Markets, 1M Edition, New
York, Springer Verlang.
Gallati, R., 2003, Risk Management & Capital Adequacy, 1st Edition, New York, McGraw-
Graham, A., Coyle, B., 2000, Venture Capital & Buyouts: Financial Risk Management and
Corporate Finance, 1SI Edition, Chicago and London, Fitzroy Dearborn Publishers.
Kohn, M., 2004, Financial Institutions and Markets, 2mt Edition, New York, Oxford
University Press.
O’Kane, D. et al. 2003, Lehman Brothers Guide to Exotic Credit Derivatives, London, Risk
Waters Group.
Seigal J.J., 2001 y Stocks fo r the Long Run, 3rd Edition, New York, McGraw-Hill
- 2 8 -
APPENDIX A: COMPANIES FOR WHOM DATA WAS COLLECTED:
r
SectorEUROPEAN CDS INDEX - DOW JONES 5- YEAR ITRAXX INDEX (16- JU N& 2006)
Company Equity Ticker 5YR CDS Tickeri Auto BAYERISCHE MOTOREN WERKE AG BMW GR EQUITY CBMW1E5 CURNCY2 Auto C1E FINANCIERE MICHELIN MIC SW EQUITY CMICH1E5 CURNCY3 Auto CONTINENTAL AG CON GR EQUITY CCONT1E5CURNCY4 Auto DAIMLERCHRYSLER AG-REG DCX GR EQUITY CDCX1E5 CURNCY
5 Auto GKNPLC GKN LN EQUITY CGKN1E5CURNCY6 Auto PEUGEOT SA UGFP EQUITY CPEUG1E5 CURNCY7 Auto RENAULT SA RNO FP EQUITY CREN1E5CURNCY
8 Auto VALEO SA FRFP EQUITY CVLOF1E5 CURNCY
9 Auto VOLKSWAGEN AG VOW GR EQUITY CVW1E5 CURNCY10 Auto VOLVO AB-B SHS VOLVB SS EQUITY CVLVY1E5 CURNCY11 Consumer ACCOR SA AC FP EQUITY CACC1E5 CURNCY12 Consumer ALTADIS SA ALT SM EQUITY CALT1E5 CURNCY13 Consumer BOOTS GROUP PLC BOOT LN EQUITY CBOTP1E5 CURNCY14 Consumer BRITISH AMERICAN TOBACCO PLC BATS LN EQUITY CBAT1E5CURNCY
15 Consumer CADBURY SCHWEPPES PLC CBRY LN EQUITY CCBRY1E5 CURNCY16 Consumer CARREPDUR SA CA FP EQUITY CCARR1E5 CURNCY17 Consumer COMPASS GROUP PLC CPGLN EQUITY CCPG1E5 CURNCY
18 Consumer DEUTSCHE LUFTHANSA-REG LHA GR EQUITY CLUFT1E5 CURNCY19 Consumer DIAGEO PLC DGE LN EQUITY CDIAG1E5 CURNCY20 Consumer DSG INTERNATIONAL PLC DSGI LN EQUITY CDIX1E5 CURNCY21 Consumer ELECTROLUX AB-SERB ELUXB SS EQUITY CELT1E5CURNCY22 Consumer GALLAHER GROUP PLC GLH LN EQUITY CGG1E5 CURNCY23 Consumer GROUPE AUCHAN 211642Z FP EQUITY CAUCH1E5 CURNCY24 Consumer GUS PLC GUS LN EQUITY CGUS1E5 CURNCY25 Consumer HENKEL KGAA-VOKZUG HEN3 GR EQUITY CHENK1E5 CURNCY26 Consumer IMPERIAL TOBACCO GROUP PLC IMT LN EQUITY CITOB1E5 CURNCY27 Consumer KINGFISHER PLC KGFLN EQUITY CKFIS1E5 CURNCY28 Consumer LVMH MOET HENNESSY LOUIS VUI MC FP EQUITY CMOET1E5CURNCY29 Consumer MARKS & SPENCER GROUP PLC MKS LN EQUITY CMKS1E5 CURNCY30 Consumer METRO AG MEO GR EQUITY CM TR01E5 CURNCY31 Consumer NESTLE SA-REG NESN VX EQUITY CNESN1E5 CURNCY32 Consumer PHILIPS ELECTRONICS NV PHIA NA EQUITY CPHG1E5 CURNCY33 Consumer PPR PP FP EQUITY CPRTP1E5 CURNCY34 Consumer SAFEWAY LTD SFW LN EQUITY CAYL1E5 CURNCY35 Consumer SODEXHO ALLIANCE SA SW FP EQUITY CEXH1E5CURNCY36 Consumer SVENSKA CELLULOSA AB-B SHS SCAB SS EQUITY CSCA1E5 CURNCY37 Consumer TA TE & LYLE PLC TATE LN EQUITY CTATE1E5 CURNCY38 Consumer TESCO PLC TSCO LN EQUITY CTSC01E5 CURNCY .39 Consumer THOMSON (EX-TMM) TMS FP EQUITY CTMMF1E5 CURNCY40 Consumer UNILEVER NV-CVA UNA NA EQUITY CULVR1E5 CURNCY
1 41 Energy CENTRAL AFRICAN GOLD PLC CAN LN EQUITY CCAN1E5CURNCY42 Energy E ON AG EOA GR EQUITY CEON1E5 CURNCY43 Energy EDISON SPA EDN IM EQUITY CEDN1E5CURNCY44 Energy ELECTRICITE DE FRANCE SA EDF FP EQUITY CEDF1E5 CURNCY45 Energy ENBW ENERGIE BADEN-WUERTTEMB EBK GR EQUITY CENB1E5 CURNCY46 Energy ENDESA SA ELE SM EQUITY CEND1E5CURNCY47 Energy ENEL SPA ENEL IM EQUITY CENEL1E5CURNCY48 Energy ENERGIAS DE PORTUGAL SA EDP PL EQUITY CEPOR1E5 CURNCY49 Energy FORTUM OYJ FUM1VFH EQUITY CBIRK1E5 CURNCY50 Energy GAS NATURAL SDGSA GAS SM EQUITY CGAS1E5 CURNCY51 Energy IBERDROLA SA IBE SM EQUITY CIBER1E5 CURNCY52 Energy NATIONAL GRID PLC NG> LN EQUITY CNGG1E5 CURNCY53 Energy REPSOL YPFSA REP SM EQUITY CREP1E5 CURNCY54 Energy RWE AG RWE GR EQUITY CRWE1E5 CURNCY55 Energy SUEZ SA SZE FP EQUITY CLYOE1E5 CURNCY56 Energy TECHNIP SA TEC FP EQUITY CTEC1E5 CURNCY57 Energy UNION FENOSA SA UNFSM EQUITY CUNFS1E5 CURNCY58 Energy UNITED UTILITIES PLC UU/LN EQUITY CUU1E5 CURNCY59 Energy VATTENFALL AB VATT SS EQUITY CVATT1E5CURNCY60 Energy VEOLIA ENVIRONNEMENT VIE FP EQUITY CVIVE1E5 CURNCY61 Financial ABN AMRO HOLDING NV AABA NA EQUITY CAAB1E5 CURNCY62 Financial AEGON NV AGN NA EQUITY CAEG01E5 CURNCY63 Financial ALLIANZ AG-REG ALV GR EQUITY CALZ1E5 CURNCY
- 2 9 -
APPENDIX A (cont’d): COMPANIES FOR WHOM DATA WAS COLLECTED
SectorEUROPEAN CDS INDEX D O W JONES 5-YEAR ITRAXX INDEX (16-JUNE-2006)
C om puiy Equity Ticker 5YR CDS Ticker64 Financial ASSICURAZIONI GENERALI GIM EQUITY CASS1E5 CURNCY65 Financial AVIVA PLC AV/LN EQUITY CAVL1E5 CURNCY66 Financial AXA AXA LN EQUITY CAXA1E5CURNCY67 Financial BANCA INTESA SPA BIN IM EQUITY CBCI1E5 CURNCY68 Financial BANCA MONTE DEI PASCHI SIENA BMPS IM EQUITY CBMP1E5 CURNCY69 Financial BANCA POPOLARE ITALIAN A BPI IM EQUITY CBPL1E5 CURNCY70 Financial BANCO BILBAO VIZCAYA ARGENTA BBVA SM EQUITY CBBVA1E5CURNCY71 Financial BANCO COMERCIAL PORTUGUES-R BCP PL EQUITY CBCP1E5 CURNCY72 Financial BANCO ESPIRITO SANTO-REG BESNN PL EQUITY CESP1E5 CURNCY73 Financial BANCO SANTANDER CENTRAL HISP SAN SM EQUITY CBSH1E5 CURNCY74 Financial BARCLAYS PLC BARC LN EQUITY CBAR1E5 CURNCY75 Financial BAYERISCHE HYPO- UND VEREINS VHB GR EQUITY CHVB1E5 CURNCY76 Financial CAPITALIA SPA CAP IM EQUITY CROM1E5 CURNCY77 Financial COMMERZBANK AG CBKGR EQUITY CCMZ1E5 CURNCY78 Financial DEUTSCHE BANK AG-REGISTERED DBKGR EQUITY CDB1E5 CURNCY79 Financial HANNOVER RUECKVERSICHERU-REG HNR1 GR EQUITY CHAN1E5CURNCY80 Financial MUENCHENER RUECKVER AG-REG MUV2 GR EQUITY CMURE1E5 CURNCY81 Financial ROYAL BANK OF SCOTLAND GROUP RBS LN EQUITY CRBS1E5 CURNCY82 Financial SANPAOLO IMI SPA SPI IM EQUITY CSAN1E5 CURNCY83 Financial SWISS RE-REG RUKN VX EQUITY CRUK1E5 CURNCY84 Financial UNICREDITO ITALIANO SPA UC IM EQUITY CUNI1E5 CURNCY85 Financial ZURICH VERSICHERUNGS-GESELLS 1010Q SW EQUITY CZUR1E5 CURNCY86 Industrial ADECCO SA-REG ADEN VX EQUITY CAD01E5 CURNCY
| 87 Industrial AKZO NOBEL AKZA NA EQUITY CAKZ01E5 CURNCY88 Industrial ARCELOR LORFP EQUITY CLOR1E5 CURNCY89 Industrial BAA PLC BAA LN EQUITY CBAA1E5 CURNCY90 Industrial BAE SYSTEMS PLC BA/LN EQUITY CBAE1E5 CURNCY91 Indus trial BAYERAG BAY GR EQUITY CBAYR1E5 CURNCY92 Industrial CIBA SPECIALTY CHEM1CALS-REG CIBN VX EQUITY CCIBA1E5 CURNCY93 Industrial COMPAGNIE DE SAINT-GOBA1N SGO FP EQUITY CGOB1E5 CURNCY94 Industrial DEGUSSA AG DGXGR EQUITY CDEG1E5 CURNCY
i 95 Industrial EUROPEAN AERONAUTIC DEFENCE EAD FP EQUITY CAER1E5 CURNCY96 Industrial FINMECCANICA SPA FNC IM EQUITY CFMEC1E5 CURNCY97 Industrial GLENCORE INTERNATIONAL AG 1696Z SW EQUITY CTE35596 CURNCY98 Industrial IMPERIAL CHEMICAL INDS PLC ICI LN EQUITY CICI1E5 CURNCY99 Industrial LAFARGE SA LG FP EQUITY CLAFS1E5 CURNCY100 Industrial LINDE AG LIN GR EQUITY CLIND1E5 CURNCY101 Industrial RENTOKIL INITIAL PLC RTO LN EQUITY CRENT1E5CURNCY102 Industrial SANOFI-AVENTIS SAN FP EQUITY CAVE 1E5 CURNCY103 Industrial SIEMENS AG-REG SIEGR EQUITY CSIEM1E5 CURNCY104 Industrial STORA ENSO OYJ-RSHS STERVFH EQUITY CSTOR1E5 CURNCY
1 105 Industrial UPM-KYMMENE OYJ U PM IV FH EQUITY CUPMK1E5 CURNCY! 106 TMT BERTELSMANN AG BTGGR EQUITY CBTG1E5 CURNCY
107 TM T BT GROUP PLC BT/A LN EQUITY CBT1E5 CURNCY108 TM T DEUTSCHE TELEKOM AG-REG DTE GR EQUITY CDT1E5CURNCY109 TM T FRANCE TELECOM SA FTE FP EQUITY CFTEL1E5 CURNCY110 TM T HELLENIC TELECOMMUN ORGANIZA HTO GA EQUITY COTE1E5 CURNCY111 TM T ITV PLC ITVLN EQUITY CCCM1E5 CURNCY112 TM T KONINKLIJKE KPN NV KPN NA EQUITY CKPN1E5 CURNCY113 TM T NOKIA OYJ NOK1VFH EQUITY CNOKI1E5 CURNCY114 TM T 0 2 PLC OOM LN EQUITY CM M 01E5 CURNCY115 TM T PEARSON PLC PSON LN EQUITY CPSON1E5 CURNCY116 TM T PORTUGAL TELECOM SGPS SA-REG PTC PL EQUITY CPORT1E5 CURNCY117 TM T REED ELSEVIER PLC REL LN EQUITY CREEDIES CURNCY118 TM T REUTERS GROUP PLC RTRLN EQUITY CRTR1E5 CURNCY119 TMT TELECOM ITALIA SPA TIT IM EQUITY CTIIM1E5 CURNCY120 TM T TELEFONICA SA TEFSM EQUITY CTLF01E5 CURNCY121 TM T TELIASONERA AB TLSN SS EQUITY CTLIA1E5 CURNCY122 TM T VIVENDI SA VIVFP EQUITY CVIVU1E5 CURNCY123 TM T VODAFONE GROUP PLC VOD LN EQUITY CVOD1E5CURNCY124 TMT WOLTERS KLUWER WLSNC NA EQUITY CWOLK1E5 CURNCY125 TM T W PP GROUP PLC W PP LN EQUITY CWPP1E5 CURNCY
APPENDIX A (cont’d): COMPANIES FOR WHOM DATA WAS COLLECTED:
SectorAMERICAN CDS INDEX - D O W JONES 5-YEAR CDX INDEX (16-JUNE-2006)
Com pany Equity Ticker SYR CDS Ticker1 Financials ACE LTD ACE US EQUITY CACE1U5 CURNCY2 Financials AETNA INC A ET US EQUITY CAET1U5CURNCY3 Industrial ALCAN INC AL US EQUITY CAL1U5 CURNCY4 Industrial ALCOA INC AA US EQUITY CAA1U5CURNCY5 Financial ALLSTATE CORP ALL US EQUITY CALL 1U5CURNCY6 TM T ALLTEL CORP A T US EQUITY CAT1U5 CURNCY7 Consumer ALTRIA GROUP INC MO US EQUITY CM 01U5 CURNCY8 Energy AMERICAN ELECTRIC POW ER AEP US EQUITY CAEP1U5 CURNCY9 Financial AMERICAN EXPRESS CO AXP US EQUITY CAXP1U5CURNCY10 Financial AMERICAN INTERNATIONAL GROUP AIG US EQUITY CAIG1U5 CURNCY11 Consumer AMGEN INC AMGN US EQUITY CAMG1U5 CURNCY12 Energy ANADARKO PETROLEUM CORP APC US EQUITY CAPC1U5 CURNCY13 TM T ARROW ELECTRONICS INC ARW US EQUITY CARW1U5 CURNCY14 TM T A T& T INC T US EQUITY CATT1U5CURNCY15 Consumer AUTOZONE INC AZO US EQUITY CAZ01U5CURNCY16 Consumer BAXTER INTERNATIONAL INC BAX US EQUITY CBAX1U5CURNCY17 Industrial BOEING CO BA US EQUITY CBA1U5 CURNCY18 Consumer BRISTOL-MYERS SQUIBB CO BMY US EQUITY CBMY1U5 CURNCY19 Industrial BURLINGTON NORTHERN SANTA FE BNI US EQUITY CBNI1U5 CURNCY20 Consumer CAMPBELL SOUP CO CPB US EQUITY CCPB1U5 CURNCY21 Financial CAPITAL ONE FINANCIAL CORP COF US EQUITY CCOF1U5 CURNCY22 Consumer CARDINAL KEALTH INC CAH US EQUITY CCAH1U5 CURNCY23 Consumer CARNIVAL CORP. CCL US EQUITY CCCL1U5 CURNCY24 Industrial CATERPILLAR INC CAT US EQUITY CCAT1U5 CURNCY25 TM T CBS CORP-CLASS B CBS US EQUITY CVIA1U5 CURNCY26 Consumer CENDANT CORP CD US EQUITY CCD1U5 CURNCY27 Industrial CENTEX CORP CTX US EQUITY CCTX1U5CURNCY28 TM T CENTURYTELINC CTL US EQUITY CCTL1U5 CURNCY29 Financial CHUBB CORP CB US EQUITY CCB1U5 CURNCY30 Financial CIGNA CORP Cl US EQUITY CCI1U5 CURNCY31 TM T CINGULAR WIRELESS CNG US EQUITY CCNG1U5CURNCY32 Financial CIT GROUP INC CIT US EQUITY CCIT1U5 CURNCY33 TM T CLEAR CHANNEL COMMUNICATIONS CCU US EQUITY CCCU1U5 CURNCY34 TM T COMCAST CABLE COMMUNICATIONS INC. CMC US EQUITY CCMC1U5 CURNCY35 TM T COMPUTER SCIENCES CORP CSC US EQUITY CCSC1U5 CURNCY36 Consumer CONAGRA FOODS INC CAG US EQUITY CCAG1U5 CURNCY37 Energy CONOCOPHILLIPS COP US EQUITY CCOC1U5 CURNCY38 Energy CONSTELLATION ENERGY GROUP CEG US EQUITY CCEG1U5 CURNCY39 Financial COUNTRYWIDE FINANCIAL CORP CFC US EQUITY CCCR1U5 CURNCY40 TM T COX COMMUNICATIONS INC-CL A COX US EQUITY CCOX1U5CURNCY41 Industrial CSX CORP CSX US EQUITY CCSX1U5 CURNCY42 -Consumer CVSCORP CVS US EQUITY CCVS1U5 CURNCY43 Industrial DEERE & CO DE US EQUITY CDE1U5 CURNCY44 Energy DEVON ENERGY CORPORATION DVN US EQUITY CDVN1U5CURNCY45 Energy DOMINION RESOURCES INC/VA D US EQUITY CDR1U5 CURNCY46 Industrial DOW CHEMICAL D OW US EQUITY CDOW1U5 CURNCY47 Industrial DU PONT (E .I0 DE NEMOURS DD US EQUITY CDD1U5CURNCY48 Energy DUKE ENERGY CORP DUK US EQUITY CDUK1U5CURNCY49 Industrial EASTMAN CHEMICAL COMPANY EMN US EQUITY CEMN1U5 CURNCY50 Financial EQUITY OFFICE PROPERTIES TR EOP US EQUITY CEOP1U5 CURNCY51 Financial FANNIE MAE FNM US EQUITY CFNMA1U5 CURNCY52 Consumer FEDERATED DEPARTMENT STORES FD US EQUITY CFD1U5 CURNCY53 Energy FIRSTENERGY CORP FE US EQUITY CFE1U5 CURNCY54 Financial FREDDIE MAC FRE US EQUITY CFHLM1U5 CURNCY55 Consumer GAP INCH"HE GPS US EQUITY CGPS1U5 CURNCY56 Financial GENERAL ELECTRIC CO GE US EQUITY CGE1U5 CURNCY57 Consumer GENERAL MILLS INC GIS US EQUITY CGIS1U5 CURNCY58 Industrial GOODRICH CORP GR US EQUITY CGR1U5 CURNCY59 Energy HALLIBURTON CO HAL US EQUITY CHAL1U5CURNCY60 Consumer HARRAH'S ENTERTAINM ENT INC H ET US EQUITY CHE1U5 CURNCY61 Financial HARTFORD FINANCIAL SVCS GRP HIG US EQUITY CHIG1U5 CURNCY62 TM T HEW LETT-PACKARD CO HPQ US EQUITY CHWP1U5 CURNCY63 Industrial HONEYWELL INTERNATIONAL INC HON US EQUITY CHON1U5CURNCY64 TM T IAC/INTERACTIVE CORP. IACI US EQUITY CIACI1U5 CURNCY65 Industrial INGERSOLL-RAND CO LTD-CL A IR US EQUITY CIR1U5 CURNCY66 Industrial INTERNATIONAL PAPER CO IP US EQUITY CIP1U5 CURNCY67 TM T INTL BUSINESS MACHINES CORP IBM US EQUITY CIBM1U5 CURNCY68 Financial INTL LEASE FINANCE CORP. ILFC US EQUITY CAIG1U5 CURNCY69 Consumer JONES APPAREL GROUP INC JNY US EQUITY CJNY1U5 CURNCY70 TM T KNIGHT RIDDER INC KRI US EQUITY CKRI1U5 CURNCY71 Consumer KRAFT POODS INC-A KFT US EQUITY CKFT1U5 CURNCY
-31 -
APPENDIX A (cont’d): COMPANIES FOR WHOM DATA WAS COLLECTED:
SectorAMERICAN CDS INDEX - D O W JONES 5-YEAR CDX INDEX (16-JUNE-2006)
Comgrajiy Equity T icker SYR CDS Ticker64 TM T IAC/INTERACTIVE CORP. IACI US EQUITY CIACI1U5 CURNCY65 Industrial INGERSOLL-RAND CO LTD-CL A IRUS EQUITY CIR1U5 CURNCY66 Industrial INTERNATIONAL PAPER CO IP US EQUITY CIP1U5 CURNCY67 TM T INTL BUSINESS MACHINES CORP IBM US EQUITY CIBM1U5 CURNCY68 Financial 1NTL LEASE FINANCE CORP ILTC US EQUITY CAIG1U5 CURNCY69 Consumer JONES APPAREL GROUP INC JNY US EQUITY CJNY1U5 CURNCY70 TM T KNIGHT RIDDERINC KRI US EQUITY CKRI1U5 CURNCY71 Consumer KRAFT FOODS INC-A K iT US EQUITY CKFT1U5 CURNCY72 Consumer KROGERCO KR US EQUITY CKR1U5 CURNCY73 Industrial LENNAR CORP-CL A LEN US EQUITY CLEN1U5 CURNCY74 Consumer LIM ITED BRANDS INC LTD US EQUITY CLTD1U5 CURNCY75 Industrial LOCKHEED MARTIN CORP LM T US EQUITY CLMT1U5 CURNCY76 Financial LOEWS CORP LTR US EQUITY CLTR1U5 CURNCY77 Consumer MARRIOTT INTERNATIONAL-CL A M AR US EQUITY CMAR1U5 CURNCY78 Financial MARSH & MCLENNAN COS MMC US EQUITY CMMC1U5 CURNCY79 Financial MBIA INSURANCE CORP. MBI US EQUITY CMBI1U5 CURNCY80 Consumer MCDONALD'S CORP MCD US EQUITY CMCD1U5 CURNCY81 Consumer MCKESSON CORP MCKUS EQUITY CMCK1U5 CURNCY82 I mils trial MEADWESTVACO CORP MWV US EQUITY CMWV1U5 CURNCY
cn00 Financial M ETLIFE INC M ET US EQUITY CMET1U5 CURNCY84 TM T MOTOROLA INC M OT US EQUITY CMOT1U5 CURNCY85 Energy NATIONAL RURAL UTILITIES COOP 2381A US EQUITY CNRUC1U5 CURNCY86 Consumer NEWELL RUBBERMAID INC NWL US EQUITY CNWL1U5 CURNCY87 TM T NEWS CORP-CLASS B NWS US EQUITY CNCP1U5 CURNCY88 Consumer NORDSTROM INC JWN US EQUITY CJWN1U5 CURNCY89 Industrial NORFOLK SOUTHERN CORP NSC US EQUITY CNSC1U5 CURNCY90 Industrial NORTHROP GRUMMAN CORP NOC US EQUITY CNOC1U5 CURNCY91 I nit OMNICOM GROUP OMC US EQUITY COMC1U5 CURNCY92 Energy PROGRESS ENERGY INC PGN US EQUITY CPGN1U5CURNCY93 Industrial PULTE HOMES INC PHM US EQUITY CPHM1U5 CURNCY94 Consumer RADIOSHACK CORP RSH US EQUITY CRSH1U5 CURNCY95 Industrial RAYTHEON COMPANY RTN US EQUITY CRTN1U5 CURNCY96 Industrial ROHM AND HAAS CO ROH US EQUITY CROH1U5CURNCY97 Consumer SABRE HOLDINGS CORP-CL A TSGUS EQUITY CTSG1U5 CURNCY98 Consumer SAFEWAY INC SWY US EQUITY CSWY1U5 CURNCY99 Consumer SARA LEE CORP SLE US EQUITY CSLE1U5 CURNCY100 Energy SEMPRA ENERGY SRE US EQUITY CSRE1U5 CURNCY101 Industrial SHERWIN-WILLIAMS CO/THE SHW US EQUITY CSHW1U5 CURNCY102 Financial SIMON PROPERTY GROUP INC SPG US EQUITY CSPG1U5 CURNCY103 Consumer SOUTHWEST AIRLINES CO LUV US EQUITY CLUV1U5 CURNCY104 TM T SPRINT NEXTEL CORP S US EQUITY CFON1U5 CURNCY105 Consumer SUPERVALU INC SVU US EQUITY CSVU1U5 CURNCY106 Consumer TARGET CORP TG TU S EQUITY CTGT1U5 CURNCY107 Industrial TEMPLE-INLAND INC TIN US EQUITY CTIN1U5 CURNCY108 Industrial TEXTRON INC TX T US EQUITY CTXT1U5CURNCY109 TM T THE WALT DISNEY CO. DIS US EQUITY CDIS1U5 CURNCY110 TM T TIM E WARNER INC TW X US EQUITY CAOL1U5 CURNCY111 Industrial TOLLS BROTHERS INC. TOL US EQUITY CTOL1U5 CURNCY112 Energy TRANSOCEAN INC RIG US EQUITY CRIG1U5 CURNCY113 TM T TRIBUNE CO TRB US EQUITY CTRB1U5 CURNCY114 Consumer TYSON FOODS INC-CL A TSN US EQUITY CTSN1U5 CURNCY115 Industrial UNION PACIFIC CORP UNP US EQUITY CUNP1U5 CURNCY116 Energy VALERO ENERGY CORP VLO US EQUITY CVL01U5 CURNCY117 TM T VERIZON COMMUNICATIONS INC VZ US EQUITY CVZGF1U5 CURNCY
. u s Consumer WAL-MART STORES INC WMT US EQUITY CWMT1U5 CURNCY119 Financial WASHINGTON MUTUAL INC WM US EQUITY CWM1U5 CURNCY120 Financial WELLS FARGO & COMPANY WFC US EQUITY CWFC1U5 CURNCY121 Consumer WENDY'S INTERNATIONAL INC WEN US EQUITY CWEN1U5 CURNCY122 Industrial WEYERHAEUSER CO WY US EQUITY CWY1U5 CURNCY123 Consumer WHIRLPOOL CORP WHRUS EQUITY CWHR1U5 CURNCY124 Consumer WYETH WYE US EQUITY CAHP1U5 CURNCY125 Financial XL CAPITAL LTD -CLASS A XL US EQUITY CXL1U5 CURNCY
- 3 2 -
APPENDIX B: SAMPLE OF INPUT DATA
Company: VOLKSWAGEN AG| S ector: Autos
Equity T icke r: VOW GR EQUITYSYR CDS TICKER: C W /1F5 INDEX
Do!o L qu lty Closin i) P tlco COS Mid P lica10/01/04 31 35 65 61io /o e /m 34.00 64.4510/15434 34 70 65.6910/22/04 33 95 69 0610/29/04 34 90 66 3711/05/04 35 20 65 7111/12/04 356 0 66.0311/19/04 34.65 66 1311/26/04 34 25 65.5612/03/04 34 31 64 4712/10X14 33 71 64.4212/17/04 33.55 65 8012/24/04 33 00 66 6812/31/04 33 35 66 6001/07/05 35 94 65 8401/14/05 35.39 63 5901/21/05 35 64 62 3101/29/05 35 86 55.5002/04/05 36 54 49 7502/11/05 37 30 40 6002/10/05 37 66 47.1702/25/05 37 10 47,0003X34X35 37 36 43 0003/11/05 36.16 44.3703/ 10x35 35 32 50.0003/25/05 36.69 56.75D4X31X15 36 46 63.1104/08/05 35.66 57.3304/15/05 34 21 09 2704/22/05 32 43 64.5504/29/05 322 2 71.7405/06/05 33 64 75.7105/13/05 34.17 77.0605/20,05 35 80 71 .B805/27/05 35 43 61 3306X33/05 36.15 56.2506/10/05 36 62 55.3706/17/05 37 40 53.3106/24/05 37 94 56 3207/01/05 30 36 55.9707/GB/05 38 06 53.1707/15/05 40 60 50 7507/22/05 42 23 52.7407/29/05 4471 52.9708/05X35 44 00 53.3000/12/05 44 41 52.7700/19/05 43 98 53 0400/26/05 42 95 52 5409/02/05 42 35 53 8709/09/05 45 20 49.9609/16/05 45 0B 46-4609/23/05 51 55 50 2309/30/05 51.33 44 0010/07/05 49 77 45 9510/14/05 47 42 47.7710/21/05 45.75 45 3510/28/05 44 74 45 5411/Q4/05 45.41 43 9711/11/05 45 66 44 6911/18/05 44 21 46 5211/25XJ5 4384 45.3512/02A35 46 50 44 0812X39X35 46 71 44 3512/16/05 44 96 42 9612/23/05 44 33 44 5512/30X35 44 61 44.5001/06/06 45 35 43.0401/13X36 47 59 42 2701/20/06 45 70 42.0801/27/06 49 04 40 0002X33X36 49 19 38.4102/10/06 54 70 37.9502/17X35 59 30 36 1202/24X36 50 97 34 3203/03X36 55 65 33.7103/10X36 55 90 34.1703/17/06 58 20 33 4003/24/06 61 96 33.3703/31X36 61 90 32.4804X37X36 63 01 30.2704/14X36 62 35 28.7904/21X36 63 96 28 3504/20/06 61 49 25 0005X35X36 50 60 26.1005/12X36 50.23 26.6605/19X36 54 10 29.2505/26/06 55 70 29.7306X32X36 54 75 28 6806/09/06 52 32 29.2506/16X36 52 90 30.69
Oato Equity CIosJimj P lico COS M ill P iice01/03/03 37.90 58 6001/10/03 36 36 59 0001/17/03 36.68 58 BO01/24/03 34 30 60 9001/31/03 38 5B 64 1402/07/03 35.74 64 9002/14X33 35.58 67 7102/21X33 37.B5 65 2002/28X33 37.10 68 0803X37X33 33.00 75.8603/14X33 29 50 87 7003/21X13 33.30 79 1003/28X33 30.75 79 7504/04/03 31.95 76 0704/11X33 32 00 73 2904/10/03 33 02 65 5004/25/03 31 22 63.0005X32/03 30.76 67 0005X19/03 32 33 65 3305/16X33 30 84 71 7505/23/03 30 12 73 3605/30/03 30.71 71 0006/06/03 32 15 6B 57D6/13X33 33 67 72 0006/20/03 35.95 66 2106/27/03 36 26 73 7907X34/03 37 41 72 3807/11/03 37 23 72 ODD7/18/03 36 68 67 0007/25X33 36 80 57 9400X31X33 38 15 55 5008X38/03 37 72 55 0800/15X33 42 25 53 50D0/22/D3 44 59 50 0000/29X33 44 66 45.7909/05/03 4570 41 2909/12X33 43 30 45 4409/19X33 43.50 43 9609/26X13 39.56 54 1010/03/03 40 35 61 3310/10/03 41 54 60 0210/17/03 43.10 48 0610/24X13 41 99 51.0510/31/03 43 39 47 5111/07/03 44 85 47 6611/14X33 45.00 44 4411/21X33 41.65 46 4211/28X33 41.45 46.8312/05X13 42.80 44 4412/12X33 43.BO 451 312/19X33 44.42 46.1512/26/03 43 40 45 4401X12/04 44 60 45 B701/09X14 41.30 46 9401/16X34 43.20 56 2501/23/04 41 20 57 9801/30X34 40 50 59 8302/06/04 39 35 64.1802/13X34 39.70 65.6502/20X34 38 90 66 1002/27X34 38.10 67 4603X35X34 39 00 65 8403/12/04 36 60 72 0403/19/04 35.70 68 8003/26/04 34 80 65 9604/02/04 36 45 61 4204/09X34 36 64 60 3104/16X34 37 72 60 8004/23/04 38 74 60.1904/30/04 36 70 63 2405/07/04 35.92 66 0706/14/04 35.38 70 2805/21X34 34.85 69 5205/28/04 35.72 60 0006X34/04 35 90 699 706/11/04 35 34 66 5306/10434 34 05 67 28D6/25X14 34.25 66 3507X32X34 33 76 69 8007X39X34 33.10 74 5607/16434 32 00 70.9407/23/04 33 00 722007/30/04 33.65 69.0008X36X34 32.45 69 7000/13/04 30 70 71 1308/20X34 30.90 67 2508/27X14 32 29 65 4409/03/04 31.95 61.6709/10/04 32.65 60 6009/17X34 32.41 6 27 909/24/04 31.54 64.32
-33 -
APPENDIX C: COMPANIES ELIMINATED FROM ORIGINAL DATA
The following companies were eliminated from the original pool of data through lack of
data. This lack of data was a result of either (a) an unreliable CDS price input or (b) the
company is no longer publicly quoted although it still has publicly quoted debt and hence
still has a quoted CDS price:
European Companies: US Companies:
1. Groupe Auchan 1. Carnival Corporation
2. Central African Gold Pic 2. Consolidated Natural Gas
3. EDF SA company
4. Vattanfall AB 3. Commercial Metals Company
5. Glencore International 4. Computer Sciences corp.
6. Bertelsmann AG 5. Knight Ridder Coq->.
6. IAC/Interactive Corp
7. Int’l Lease Finance Corp.
8. MBIA Insurance Corp.
9. National Rural Utility Coop
10. Toll Brothers Inc
11. Wendy’s International Inc.
- 3 4 -
APPENDIX D: REGRESSION ANALYSIS OUTPUTS
Company: Alcoa Inc.
Sector: Industrial (Metal - Aluminium)
Company Description: Alcoa Inc. produces primary aluminium, fabricated
aluminium, and alumina, and participates in mining, refining,
smelting, fabricating and recycling. The company serves
customers world-wide primarily in the transportation,
packaging, building, and industrial markets with both
fabricated and finished products.
Bloomberg Equity Ticker: AA US EQUITY (Independent Variable)
Bloomberg 5YR CDS Ticker: CAA1U5 CURNCY (Dependent Variable)
Regression Outputs:Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 ,73 6(a) .542 .539 8.14853a Predictors: (Constant), Px Last
ANOVA(h)
ModelSum of Squares df Mean Square F —
1 Regression 16393.796 1 16393.796 246.900 .000(a)Residual 13877.300 209 66.399Total 30271.096 210
a Predictors: (Constant), Px Last b Dependent Variable: Px Mid
Coel'ficients(a)Unstandardized
CoefficientsStandardizedCoefficients
Model B Std. Error Beta t Sig.1 (Constant) 90.992 3.671 24.790 .000
Px Last -1.982 .126 -.736 -15.713 .000a Dependent Variable: Px Mid
- 3 5 -
APPENDIX D (cont’d): REGRESSION ANALYSIS OUTPUTS
Company: American Express
Sector: Financial (Finance - Credit Card)
Company Description: American Express company, through its subsidiaries,
provides travel-related financial advisory, and international
banking services around the world. The company’s products
include the American Express Card, the Optima Card and the
American Express Travellers Cheque.
Bloomberg Equity Ticker: AXP US EQUITY (Independent Variable)
Bloomberg SYR CDS Ticker: CAXP1U5 CURNCY (Dependent Variable)
Regression Outputs:Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 .828(a) .686 .685 11.18564a Predictors: (Constant), Px Last____________________ ___________________ ANOVA(b)
ModelSum of Squares df Mean Square F Sig.
1 Regression 56867.420 1 56867.420 454.508 .000(a)Residual 26024.677 208 125.119
Total 82892.097 209a Predictors: (Constant), Px Last b Dependent Variable: Px Mid________________________________________Cocfficients(a)
UnstandardizedCoefficients
StandardizedCoefficients
Model B Std. Error Beta t Si,.1 (Constant) 125.334 4.342 28.865 .000
Px Last -2.137 .100 -.828 -21.319 .000a Dependent Variable: Px Mid
- 3 6 -
APPENDIX D (cont’d): REGRESSION ANALYSIS OUTPUTS
Company: The Boeing Company
Sector: Consumer (Aerospace - Defence)
Company Description: The Boeing Company, together with its subsidiaries,
develops, produces, and markets commercial jet aircraft, as
well as provides related support services to the commercial
airline industry world-wide. The company also researches,
develops, produces, modifies, and supports information,
space, and defence systems, including military aircraft,
helicopters and space missile systems.
Bloomberg Equity Ticker: BA US EQUITY (Independent Variable)
Bloomberg 5YR CDS Ticker: CBA1U5 CURNCY (Dependent Variable)
Regression Outputs:______________________ Model Summary___________________
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 .757(a) .572 .570 21.4402a Predictors: (Constant), Px Last
____________________ ________________ANOVA(b)Sum of
Model Squares df Mean Square F Si,.1 Regression 127955.02
1 1 127955.021 278.356 .000(a)
Residual 95613.543 208 459.680Total 223568.56
5 209
a Predictors: (Constant), Px Last b Dependent Variable: Px Mid
Cocfticicnts(a)Unstandardized
CoefficientsStandardizedCoefficients
Model B Std. Error Beta t Sig.1 (Constant) 122.076 4.873 25.053 .000
Px Last -1.561 .094 -.757 -16.684 .000a Dependent Variable: Px Mid
- 3 7 -
APPENDIX D (cont’d): REGRESSION ANALYSIS OUTPUTS
Company: Hewlett Packard Company.
Sector: TMT (Computers and related hardware.)
Company Description: Hewlett-Packard Company provides imaging and printing
systems, computing systems, and information technology
services for business and home. The company’s products
include laser and inkjet printers, scanners, copiers and faxes,
personal computers, workstations, storage solutions, and
other computing and printing systems. Hewlett-Packard sells
it’s products world-wide.
Bloomberg Equity Ticker: HPQ US EQUITY (Independent Variable)
Bloomberg 5YR CDS Ticker: CHWP1U5 CURNCY (Dependent Variable)
Regression Outputs:______________________Model Summary__________________
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 .664(a) .440 .438 27.0703a Predictors: (Constant), Px Last
ANOVA(b)
Sum ofModel Squares df Mean Square F Sig.1 Regression 120489.27
3 1 120489.273 164.422 .000(a)
Residual 153155.814 209 732.803
Total 273645.087 210
a Predictors: (Constant), Px Last b Dependent Variable: Px Mid
Coefficients(a)Unstandardized
CoefficientsStandardizedCoefficients
Model B Std. Error Beta t Sig.1 (Constant) 143.691 7.930 18.121 .000
Px Last -4.509 .352 -.664 -12.823 .000a Dependent Variable: Px Mid
- 3 8 -
APPENDIX D (cont’d): REGRESSION ANALYSIS OUTPUTS
Company: The Kroger Company
Sector: Consumer (Food - Retail)
Company Description: The Kroger company operates supermarkets and convenience
stores in the United States. The company also manufactures
and processes food that its supermarkets sell. Kroger’s stores
operate under names such as Dillon Food Stores, City
Market, Sav-Mor, Kwik Shop and Mini Mart.
Bloomberg Equity Ticker: KR US EQUITY (Independent Variable)
Bloomberg 5YR CDS Ticker: CKR1U5 CURNCY (Dependent Variable)
Regression Outputs:Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 .312(a) .097 .093 26.77410a Predictors: (Constant), Px Last
ANOVA(b)
ModelSum of
Squares df Mean Square F Sig.1 Regression 17103.991 1 17103.991 23.860 .000(a)
Residual 158424.345 221 716.852
Total 175528.337 222
a Predictors: (Constant), Px Last b Dependent Variable: Px Mid
Coefficients(a)Unstandardized
CoefficientsStandardizedCoefficients
Model B Std. Error Beta t Sig.1 (Constant) 140.891 14.259 9.881 .000
Px Last -3.897 .798 -.312 -4.885 .000a Dependent Variable: Px Mid
- 3 9 -
APPENDIX D (cont’d): REGRESSION ANALYSIS OUTPUTS
Company: National Grid Pic.
Sector: Energy (Electric Distribution)
Company Description: National Grid Pic owns. Operates and develops electricity
and gas networks. The group’s electricity transmission and
gas distribution networks are located throughout the UK and
in the northeastern section of the US. They also own
liquefied natural gas storage facilities in Britain and provide
infrastructure services to the mobile telecom industry.
Bloomberg Equity Ticker: LG/ LN EQUITY (Independent Variable)
Bloomberg SYR CDS Ticker: CNGG1E5 CURNCY (Dependent Variable)
Regression Outputs:
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 .701(a) .491 .488 11.407a Predictors: (Constant), Px Last
________________ _______ ____________ANOVA(b)
ModelSum of
Squares df Mean Square F Sig.1 Regression 25599.362 1 25599.362 196.724 .000(a)
Residual 26546.212 204 130.128Total 52145.574 205
a Predictors: (Constant), Px Last b Dependent Variable: Px Mid
Coeffictents(a)Unstandardized
CoefficientsStandardizedCoefficients
Model B Std. Error Beta t Sig.1 (Constant) 121.372 5.831 20.815 .000
Px Last -11.748 .838
oNi" -14.026 .000a Dependent Variable: Px Mid
- 4 0 -
APPENDIX D (cont’d): REGRESSION ANALYSIS OUTPUTS
Company: PPR (Pinault-Printemps-Redoute)
Sector: Consumer (Retail - Major Department Store)
Company Description: PPR SA retails consumer and household products, sporting
goods, personal computers, lingerie and other luxury goods
by Gucci, Yves Saint-Laurent, Bottega Venata, Balenciaga,
and Sergio Rossi.
Bloomberg Equity Ticker: PP FP EQUITY (Independent Variable)
Bloomberg 5YR CDS Ticker: CPRTP1E5 CURNCY (Dependent Variable)
Regression Outputs:
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 .808(a) .653 .651 43.862a Predictors: (Constant), Px Last
ANQVA(b)Sum of
Model Squares df Mean Square F Sig.1 Regression 648793.96
4 1 648793.964 337.232 .000(a)
Residual 344374.079 179 1923.878
Total 993168.043 180
a Predictors: (Constant), Px Last b Dependent Variable: Px Mid
Coefficients(a)Unstandardized
CoefficientsStandardizedCoefficients
Model B Std. Error Beta t Sig.1 (Constant)
Px Last563.004
-5.49224.243
.299 -.80823.223
-18.364.000.000
a Dependent Varia jle: Px Mic
-41 -
APPENDIX D (cont’d): REGRESSION ANALYSIS OUTPUTS
Company: Siemens AG.
Sector: Industrial (Diversified Manufacturing Operations)
Company Description: Siemens AG manufactures a wide range of industrial and
consumer products. The company builds locomotives, traffic
control systems and automotive electronics, and engineers
electrical power plants. Siemens also provides public and
private communications networks, computers, building
control systems, medical equipment, and electrical
components. The company operates world-wide.
Bloomberg Equity Ticker: SIE GR EQUITY (Independent Variable)
Bloomberg 5YR CDS Ticker: CSIEM1E5 CURNCY (Dependent Variable)
Regression Outputs:Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 .609(a) .370 .368 14.13565a Predictors: (Constant), Px Last
____________________________________ ANOVA(b)
ModelSum of
Squares df Mean Square F Siq.1 Regression 29615.175 1 29615.175 148.212 .000(a)
Residual 50353.750 252 199.816Total 79968.925 253
a Predictors: (Constant), Px Last b Dependent Variable: Px Mid
Coefficients(a)Unstandardized
CoefficientsStandardizedCoefficients
Model B Std. Error Beta t Sig.1 (Constant) 93.803 4.970 18.875 .000
Px Last -1.016 .083 -.609 -12.174 .000a Dependent Variable: Px Mid
- 4 2 -
APPENDIX D (cont’d): REGRESSION ANALYSIS OUTPUTS
Company: Transocean Inc.
Sector: Energy (Oil & Gas Drilling)
Company Description: Transocean Inc is an offshore drilling contractor. The
company owns or operates mobile offshore drilling units,
inland drilling barges, and other assets utilised in the support
of offshore drilling activities world-wide. Transocean
specialises in technically demanding segments of the offshore
drilling business, including deepwater and harsh environment
drilling services.
Bloomberg Equity Ticker: RIG US EQUITY (Independent Variable)
Bloomberg 5YR CDS Ticker: CRIG1U5 CURNCY (Dependent Variable)
Regression Outputs:Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 .732(a) .536 .534 10.070a Predictors: (Constant), Px Last
ANOVA(b)
ModelSum of
Squares df Mean Square F Sig.1 Regression 20529.068 1 20529.068 202.430 .000(a)
Residual 17747.266 175 101.413Total 38276.334 176
a Predictors: (Constant), Px Last b Dependent Variable: Px Mid
Coefficients(a)Unstandardized
CoefficientsStandardizedCoefficients
Model B Std. Error Beta t Sig.1 (Constant) 61.939 1.719 36.035 .000
Px Last -.526 .037 -.732 -14.228 .000a Dependent Variable: Px Mid
- 4 3 -
APPENDIX D (cont’d): REGRESSION ANALYSIS OUTPUTS
Company: Unicredito Italiano SpA
Sector: Financial (Commerical Bank)
Company Description: Unicredito Italiano SpA, a bank, conducts operations in Italy.
The group’s three divisions include Unicredito Banca serving
families and small businesses, Unicredito Banca d’lmpresa
for corporate segment and public organisations and
Unicredito Private Banking for wealth management.
Unicredito is also present in Central and Eastern Europe.
Bloomberg Equity Ticker: UC IM EQUITY (Independent Variable)
Bloomberg 5YR CDS Ticker: CUNI1E5 CURNCY (Dependent Variable)
Regression Outputs:
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 .483(a) .233 .230 9.35247a Predictors: (Constant), Px Last
ANOVA(b)
ModelSum of
Squares df Mean Square F Siq
1 Regression 5911.286 1 5911.286 67.582 .000(a)Residual 19418.038 222 87.469Total 25329.324 223
a Predictors: (Constant), Px Last b Dependent Variable: mid
Coefficients(a)Un standardized
CoefficientsStandardizedCoefficients
Model B Std. Error Beta t Sig.1 (Constant) 52.956 4.027 13.151 .000
Px Last -7.447 .906 -.483 -8.221 .000a Dependent Variable: mid
- 4 4 -
APPENDIX D (cont’d): REGRESSION ANALYSIS OUTPUTS
Company: Valero Energy Corp.
Sector: Energy (Oil Refining and Marketing)
Company Description: Valero Energy Corporation is an independent petroleum
refining and marketing company that owns and operates
refineries in the United States and Canada. The company
also operates retail sites under the Valero, Diamond
Shamrock, Ultramar, Total, and Beacon Brands. In addition,
Valero owns a proprietary pipeline network.
Bloomberg Equity Ticker: VLO US EQUITY (Independent Variable)
Bloomberg 5YR CDS Ticker: CVL01U5 CURNCY (Dependent Variable)
Regression Outputs:Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 .544(a) .296 .292 56.60795a Predictors: (Constant), Px Last
ANOVA(b)
ModelSum of
Squares df Mean Square F Sig.1 Regression 281143.05
4 1 281143.054 87.735 .000(a)
Residual 669732.131 209 3204.460
Total 950875.185 210
•
a Predictors: (Constant), Px Last b Dependent Variable: Px Mid
Coefficients(a)Unstandardized
CoefficientsStandardizedCoefficients
Model B Std. Error Beta t Sig.1 (Constant) 135.740 6.557 20.701 .000
Px Last -1.976 .211 -.544 -9.367 .000a Dependent Variable: Px Mid
- 4 5 -
APPENDIX D (cont’d): REGRESSION ANALYSIS OUTPUTS
Company:
Sector:
Company Description:
Vivendi SA.
Telecommunications, Media and Technology (Multimedia)
Vivendi SA, through its subsidiaries, conducts operations
ranging from music, games, and television services, sells
music CDs, develops and distributes interactive
entertainment, and operates mobile and fixed line
telecommuni cations.
Bloomberg Equity Ticker: VIV FP EQUITY (Independent Variable)
Bloomberg 5YR CDS Ticker: CVTVU1E5 CURNCY (Dependent Variable)
Regression Outputs:
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 .607(a) .369 .366 217.76052a Predictors: (Constant), Px Last
____________________ ___________ ANOVA(b)
ModelSum of Squares df Mean Square F Sijx
1 Regression 6013359.218 1 6013359.218 126.812 .000(a)
Residual 10290062.839 217 47419.644
Total 16303422.057 218
a Predictors: (Constant), Px Last b Dependent Variable: Px Mid
Cocfficicnts(a)Unstandardized
CoefficientsStandardizedCoefficients
Model B Std. Error Beta t Sig.1 (Constant) 874.890 59.639 14.670 .000
Px Last -30.446 2.704 -.607 -11.261 .000a Dependent Variable: Px Mid
- 4 6 -
APPENDIX D (cont’d): REGRESSION ANALYSIS OUTPUTS
Company: Volkswagen AG.
Sector: Autos (Auto - Cars/Light Trucks)
Company Description: Volkswagen AG manufactures economy and luxury
automobiles, sports cars, trucks, and commercial vehicles for
sale world-wide. The company produces the Passat, Golf,
Cabrio, Jetta, GTI, Beetle, AUDI, and other Models.
Volkswagen also owns Seat and Skoda, which manufacture
and sell cars in Spain and in Southern & Eastern Europe, and
Lamborghini, which makes sports cars in Italy
Bloomberg Equity Ticker: VOW GR EQUITY (Independent Variable)
Bloomberg 5YR CDS Ticker: CVW1E5 CURNCY (Dependent Variable)
Regression Outputs:
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 .835(a) .698 .697 7.84767a Predictors: (Constant), Px Last
ANOVA(b)
ModelSum of Squares df Mean Square F Sir.
1 Regression 35269.437 1 35269.437 572.687 ,000(a)Residual 15273.295 248 61.586Total 50542.732 249
a Predictors: (Constant), Px Last b Dependent Variable: nmid
Coeffldents(a)Unstandardized
CoefficientsStandardizedCoefficients
Model B Std. Error Beta t Sig.1 (Constant) 114.283 2.554 44.743 .000
Px Last -1.421 .059 -.835 -23.931 .000a Dependent Variable: nmid
- 4 7 -
APPENDIX D (cont’d): REGRESSION ANALYSIS OUTPUTS
Cars/Light Trucks, Machinery - General
Company: Volvo AB.
Sector: Autos (Autos
Industry)
Company Description: Volvo AB manufactures, trucks, buses and industrial engines,
and aerospace equipment. The company also offers repair
and maintenance, lease financing, insurance and financial
products to its customers. Volvo manufactures and markets
its products world-wide.
Bloomberg Equity Ticker: VOLVB SS EQUITY (Independent Variable)
Bloomberg 5YR CDS Ticker: CVLVY1E5 CURNCY (Dependent Variable)
Regression Outputs:
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 .771(a) .595 .593 16.02262a Predictors: (Constant), Px Last
ANOVA(b)Sum of
Model Squares df Mean Square F Sig.1 Regression 93452.021 1 93452.021 364.017 .000(a)
Residual 63667.603 248 256.724Total 157119.62
5 249
a Predictors: (Constant), Px Last b Dependent Variable: npxmid
Coefficients(a)Unstandardized
CoefficientsStandardizedCoefficients
Model B Std. Error Beta t Sig.1 (Constant) 110.206 3.267 33.736 .000
Px Last -2.350 .123 -.771 -19.079 .000a Dependent Variable: npxmid
- 4 8 -
APPENDIX D (cont’d): REGRESSION ANALYSIS OUTPUTS
Company: The Walt Disney Company
Sector: TMT (Multimedia)
Company Description: The Kroger company operates supermarkets and convenience
stores in the United States. The company also manufactures
and processes food that its supermarkets sell. Kroger’s stores
operate under names such as Dillon Food Stores, City
Market, Sav-Mor, Kwik Shop and Mini Mart.
Bloomberg Equity Ticker: KR US EQUITY (Independent Variable)
Bloomberg 5YR CDS Ticker: CKR1U5 CURNCY (Dependent Variable)
Regression Outputs:Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 .865(a) .747 .746 17.20888a Predictors: (Constant), Px Last
ANOVA(b)
ModelSum of
Squares df Mean Square F Sig.1 Regression 216426.04
6 1 216426.046 730.810 .000(a)
Residual 73147.958 247 296.146Total 289574.00
4 248
a Predictors: (Constant), Px Last b Dependent Variable: mid
Coefficients(a)Unstandardized
CoefficientsStandardizedCoefficients
Model B Std. Error Beta t Sig.1 (Constant) 237.726 6.631 35.851 .000
Px Last -7.677 .284 -.865 -27.033 .000a Dependent Variable: mid
- 4 9 -
APPENDIX E: MARKS & SPENCER GROUP LBO SPECULATION HISTORY
Figure 5 shows the graphical relationship between Marks & Spencer Group Pic’s (M&S)
equity price and CDS price:
M ark s & S p en ce r G roup P ic Equity P r ic e (L H S) v's C D S S p rea d (R H S)
1 b p = 0 .01 %
Figure 5: M&S Equity Price v. ‘s CDS Price 2001 - Present
Timeline:
27-May-2004: News breaks that billionaire Philip Green is considering making a bid for
M&S. Green owns UK fashion chains including Dorothy Perkins, Top
Shop and BHS Ltd. M&S’s share price rose €0.81 to €5.16 (+19%).
M&S’s CDS price doubled from 65bps to 130bps and continued to
increase strongly in the subsequent days.
14-Jul-2004: Philip Green withdrew his €13.18 billion offer to buy M&S after the
company rejected his advances three times in seven weeks. Philip
concluded that he would not gain the co-operation of the board at M&S.
Investors sided with M&S, then newly appointed CEO, Stuart Rose siding
with his plan to return €3.33 billion to them. M&S’s share price declined
€0.28 to €5.17 (-5%) while it’s CDS price tumbled from 198bps to 128bps
and continued to fall in the days after.
- 50-
APPENDIX F: MARKS & SPENCER REGRESSION ANALYSIS OUTPUT
Company: Marks & Spencer Group pic.
Sector: Consumer (Retail - Major Department Store)
Company Description: Marks & Spencer Group pic operates retail stores in the UK,
which sell consumer goods under the name St. Michael. The
group also provides a range of financial services, including
trust units, account cards, personal loans, pension and life
assurance. They also operate Kings super markets in the US
in addition to retail stores in the Middle East.
Bloomberg Equity Ticker: MKS LN EQUITY (Independent Variable)
Bloomberg 5YR CDS Ticker: CMKS1E5 CURNCY (Dependent Variable)
Regression Outputs:
SUB PERIOD 1: Before LBO NEWS BREAKING:
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 .057(a) .003 -.020 12.084a Predictors: (Constant), Px Last
ANOVA(b)
ModelSum of Squares df Mean Square F Sig.
1 Regression 20.337 1 20.337 .139 .711(a)Residual 6278.957 43 146.022Total 6299.294 44
a Predictors: (Constant), Px Last b Dependent Variable: Px Mid
CoefTicients(a)Unstandardized
CoefficientsStandardizedCoefficients
Model B Std. Error Beta t Sig.1 (Constant) 48.004 38.963 1.232 .225
Px Last -3.454 9.254 -.057 -.373 .711a Dependent Variable: Px Mid
-51 -
APPENDIX F (cont’d): MARKS & SPENCER REGRESSION ANALYSIS OUTPUT
SUB PERIOD 2: DURING PERIOD OF LBO SPECULATION:Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 .871(a) *759 .739 37.004a Predictors: (Constant), Px Last
ANOVA(b)
ModelSum of Squares df Mean Square F Sig.
1 Regression 51823.045 1 51823.045 37.846 .000(a)Residual 16431.919 12 1369.327Total 68254.965 13
a Predictors: (Constant), Px Last b Dependent Variable: Px Mid
Coefflcicnts(a)Unstandardized
CoefficientsStandardizedCoefficients
Model B Std. Error Beta t Sig.1 (Constant) -2449.278 426.933 -5.737 .000
Px Last 494.167 80.328 .871 6.152 .000a Dependent Variable: Px Mid
SUB PERIOD 3: PERIOD AFTER LBO SPECULTION RECEDED:Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the Estimate
1 .931(a) .866 .865 12.640a Predictors: (Constant), Px Last
ANOVA(b)Sum of
Model Squares df Mean Square F Sig.1 Regression 95050.980 1 95050.980 594.927 .000(a)
Residual 14698.754 92 159.769Total 109749.73
4 93
a Predictors: (Constant), Px Last b Dependent Variable: Px Mid
- 52 -
APPENDIX F (cont’d): MARKS & SPENCER REGRESSION ANALYSIS OUTPUT
Coel'ficients(a)Unstandardized
CoefficientsStandardizedCoefficients
Model B Std. Error Beta t1 (Constant) 235.863 6.220 37.917 .000
Px Last -24.601 1.009 -.931 -24.391 .000a Dependent Variable: Px Mid
APPENDIX G: CDS INDICES CONSTRUCTION INFORMATION
Construction Rules of Dow Jones CDX17 and ITraxx18 Indices
■ Construction via dealer liquidity poll, administered by International Index
Corporation (IIC).
■ Each market maker submits to IIC a long list of names based on the following
criteria:
1. Incorporated in USA for CDX Index and Europe for the ITraxx Index.
2. Those names with the highest CDS trading volume, as measured over the
previous 6 months.
3. Volumes for financial names are derived from Subordinated (Lower Tier 2)
transactions.
4. Exclude all internal transactions from the volume statistics, e.g. those with
an internal proprietary desk.
■ Volumes for names that fall under the same ticker, but trade separately in the CDS
market, are summed to arrive at an overall volume for each issuer.
■ The list is ranked according to trading volumes, (i.e. the issuer with the highest
trading volume first), and submitted in the form of Bloomberg corporate ticker.
■ IIC collates all submitted lists and removes any names rated Baa3/BBB and on
negative outlook.
■ Each issuer is assigned to its appropriate Dow Jones sector.
■ Each Dow Jones sector is mapped to a CDX/ITraxx sector and each issuer ranked
within its sector by averaging the liquidity ranking of the market makers.
■ The final portfolio comprises 125 issuers, and is constructed by selecting the
highest ranking issuers in each sector below:
■ For the CDX Index:
17 Source: Dow Jones Indexes Guide to Dow Jones CDX Indexes, Sept 2005.
1S Source: International Index Corporation, Dow Jones ITraxx - Portfolio Rules of Construction. July 2004.
- 5 4 -
APPENDIX G (cont’d): CDS INDICES CONSTRUCTION INFORMATION
36 Consumers
14 Energy
29 Industrials
22 TMT
24 Financials
■ And for the ITraxx Index:
10 Autos.
30 Consumers (15 cyclicals & 15 non-cyclicals).
20 Energy.
20 Industrials.
20 TMT.
25 Financials (separate Senior & Subordinated indices).
Non-Financials (100 names excl. Financials).
(E.g. the 20 highest ranking Energy issuers, and the 25 highest-ranking
Financials arc included).
■ Each name is weighted equally in the overall and sub-indices. For indices that
cannot be divided equally to two decimal places, weighting adjustments (in the
magnitude of +/- 0.01%) will be made in alphabetical order.
■ For each issuer (Bloomberg corporate ticker) the most liquid CDS reference entity
is assigned.
- 5 5 -
APPENDIX H: RATINGS DEFINITIONS
Moodys Rating Service:
Moody's Long-Term Rating Definitions:
Obligations rated Aaa are Judged to be of the highest quality, w ith m inim al credit risk.
Aa Obligations rated Aa are judged to be o f high quality and are subject to very low credit risk.
A Obligations rated A are considered upper-medium grade and are subject to low credit risk.
Baa Obligations rated Baa are subject to moderate credit risk. They are considered medium-grade and as such may possess certain speculative characteristics.
Ba Obligations rated Ba are judged to have speculative elements and are subject to substantial credit risk.
B Obligations rated B are considered speculative and are subject to high credit risk.
Caa Obligations rated Caa are judged to be o f poor standing and are subject to very high credit risk.
Ca Obligations rated Ca are highly speculative and are likely in, or very near, default, w ith some prospect o f recovery o f principal and interest.
C Obligations rated C are the lowest rated class o f bonds and are typ ica lly in default, w ith little prospect for recovery of principal or interest.
Figure 6: Moodys Investor Service Credit Rating Scale
Source: Moodys Investor Service Rating Symbols and Definitions, (August 2004)
As can be seen from figure 6 above, Moodys Rating Service definitions range from Aaa
(the highest quality credit rating) to C (the lowest rating, typically in default). If a
company or particular debt issuing is rated between Aaa and Baa, it is considered
Investment Grade. If a company of debt issue is rated Ba or below is classified as sub
investment grade (a.k.a. speculative or junk).
- 5 6 -
APPENDIX H: RATINGS DEFINITIONS
Standard & Poor's (S&P) Rating Service
Long-Term Issue Credit RatingsAn obligation rated 'AAA' has the highest rating assigned by Slandard & Poor's. The obligor's capacity to meet
AAA its financial commitment on Ihe obligation is extremely strong.
AAAn obligation rated 'AA' differs from the highest-rated obligations only to a small degree The obligor's capacity to meet its financial commitment on Ihe obligation is very strong.
A
An obligation rated 'A' is somewhat more susceptible to the adverse effects of charges in circumstances and economic conditions than obligations in higher-rated categories. However, the obligor's capacity to meet its financial commitment on the obligation is still strong.
BBB
An obligation rated 'BBB'exhibits adequate protection parameters. However, adverse economic conditions or changing circumstances are more likely to lead to a weakened capacity of the obligor to meet its financial commitment on the obligation
BB
An obligation rated 'BB' is less vulnerable to nonpayment than other speculative issues. However, it faces major ongoing uncertainties or exposure to adverse business, financial, or economic conditions which could lead to the obligor's inadequate capacity to meet its financial commitment on the obligation.
B
An obligation rated 'B' is more vulnerable to nonpayment than obligations rated 'BB', but the obligor currently has the capacity to meet its financial commitment on the obligation. Adverse business, financial, or economic conditions will likely impair the obligor's capacity or willingness to meet its financial commitment on the obligation
CCC
An obligation rated 'CCC' is currently vulnerable to nonpayment, and is dependent upon favorable business, financial, and economic conditions for the obligor to meet its financial commitment on the obligation. In the event of adverse business, financial, or economic conditions, the obligor is not likely to have the capacity to meet its financial commitment on the obligation.
CC An obligation rated 'CC' is currently highly vulnerable to nonpayment
C
A subordinated debt or preferred stock obligation rated 'C‘ is currently highly vulnerable to nonpayment. The 'C' rating may be used to cover a situation where a bankruptcy petition has been filed or similar action taken, but payments on this obligation are being continued. A ’C' also will be assigned to a preferred stock issue in arrears on dividends or sinking fund payments, but that is currently paying.
D
An obligation rated 'D‘ is in payment default. The 'D' rating category is used when payments on an obligation are not made Dn the date due even if Ihe applicable grace period has not expired, unless Standard & Poor's believes that such payments will be made during such grace period. The 'D' rating also will be used upon the filing of a bankruptcy petition or the taking of a similar action if payments on an obligation are jeopardized.
Figure 7: S&P Ratings Definitions
Source: Standard&. Poor’s website {www.ratingsdirect.com). 14 June 2006
Similar to Moodys, S&P have a rating scale as shown in figure 7, which is broken down
into investment grade and sub-investment grade. If a company/debt issue is rated between
AAA and BBB, it is considered investment grade. If a company/debt issue is rated BB or
below it is then classified as sub-investment grade.
- 5 7 -
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